Function homology screening

ABSTRACT

A method of screening biologically active agent based on the analysis of complex biological responses in culture. Methods for selecting cells and culture conditions for such screens are provided, as well as the identification of an optimized set of discrete parameters to be measured, and the use of biomap analysis for rapid identification and characterization of drug candidates, genetic sequences acting pathways, and the like. A feature of the invention is simultaneous screening of a large number of cellular pathways, and the rapid identification of compounds that cause cellular responses.

FIELD OF THE INVENTION

[0001] The field of the invention is the discrimination betweendifferent cellular pathways and their use in the determination of theeffect of agents on cell cultures.

BACKGROUND OF THE INVENTION

[0002] Pharmaceutical drug discovery, a multi-billion dollar industry,involves the identification and validation of therapeutic targets, aswell as the identification and optimization of lead compounds. Theexplosion in numbers of potential new targets and chemical entitiesresulting from genomics and combinatorial chemistry approaches over thepast few years has placed enormous pressure on screening programs. Therewards for identification of a useful drug are enormous, but thepercentages of hits from any screening program are generally very low.Desirable compound screening methods solve this problem by both allowingfor a high throughput so that many individual compounds can be tested;and by providing biologically relevant information so that there is agood correlation between the information generated by the screeningassay and the pharmaceutical effectiveness of the compound.

[0003] Some of the more important features for pharmaceuticaleffectiveness are specificity for the targeted cell or disease, a lackof toxicity at relevant dosages, and specific activity of the compoundagainst its molecular target. Therefore, one would like to have a methodfor screening compounds or libraries of compounds that allowssimultaneous evaluation for the effect of a compound on differentcellular pathways, where the assay predicts aspects of clinicalrelevance and potentially of future in vivo performance.

[0004] While collecting information about multiple aspects ofpharmacologic activity is useful because it provides a more completeanalysis of the compound, it also makes the data analysis moredifficult, because multiple parameters must be considered. Developmentsin computing technologies can provide solutions, but must be tied intothe matrix of biological information.

[0005] In addition, cellular physiology involves multiple pathways,where pathways split and join, redundancies in performing specificactions and responding to a change in one pathway by modifying theactivity of a different pathway. In order to understand how a candidatedrug is acting and whether it will have the desired effect, it isnecessary to know, not only the target protein with which the drugreacts, but whether the inhibition of the protein activity will resultin the desired response. The development of screening assays that canprovide better, faster and more efficient prediction of mechanisms ofaction, cellular effects and clinical drug performance is of greatinterest in a number of fields, and is addressed in the presentinvention. It is an object of the invention to provide a method forscreening for inhibitors or modulators of cellular processes, whichprovide multiparameter information about the action of the agents testedon multiple cellular pathways.

[0006] Relevant Literature

[0007] In many assays, cell-free components such as enzymes and theirsubstrates are used for compound screening. For example, U.S. Pat. No.4,568,649 describes ligand detection systems which employ scintillationcounting. In these methods, the therapeutic utility of compoundsidentified in such assays is presumed from a large body of otherevidence previously identifying that a particular enzyme or target maybe important to a disease process.

[0008] Cell based assays include a variety of methods to measuremetabolic activities of cells including: uptake of tagged molecules ormetabolic precursors, receptor binding methods, incorporation oftritiated thymidine as a measure of cellular proliferation, uptake ofprotein or lipid biosynthesis precursors, the binding of radiolabeled orotherwise labeled ligands; assays to measure calcium flux, and a varietyof techniques to measure the expression of specific genes or their geneproducts.

[0009] Compounds have also been screened for their ability to inhibitthe expression of specific genes in gene reporter assays. For example,Ashby et al. U.S. Pat. No. 5,569,588; Rine and Ashby U.S. Pat. No.5,777,888 describe a genome reporter matrix approach for comparing theeffect of drugs on a panel of reporter genes to reveal effects of acompound on the transcription of a spectrum of genes in the genome.

[0010] Methods utilizing genetic sequence microarrays allow thedetection of changes in expression patterns in response to stimulus. Afew examples include U.S. Pat. No. 6,013,437; Luria et al., “Method foridentifying translationally regulated genes”; U.S. Pat. No. 6,004,755,Wang, “Quantitative microarray hybridization assays”; and U.S. Pat. No.5,994,076, Chenchik et al., “Methods of assaying differentialexpression”. U.S. Pat. No. 6,146,830, Friend et al. “Method fordetermining the presence of a number of primary targets of a drug”.

[0011] Proteomics techniques have potential for application topharmaceutical drug screening. These methods require technically complexanalysis and comparison of high resolution two-dimensional gels or otherseparation methods, often followed by mass spectrometry (for reviews seeHatzimanikatis et al. (1999) Biotechnol Prog 15(3):312-8; Blackstock etal. (1999) Trends Biotechnol 17(3):121-7. A discussion of the uses ofproteomics in drug discovery may be found in Mullner et al. (1998)Arzneimittelforschung 48(1):93-5.

[0012] Various methods have been used to determine the function of agenetic sequence. The initial effort is often performed from sequenceinformation alone. Such techniques can reasonably determine if a newgene encodes a soluble or membrane-bound protein, a member of a knowngene family such as the immunoglobulin gene family or the tetraspan genefamily, or contains domains associated with particular functions (e.g.calcium binding, SH2 domains etc.). Multiple alignments against adatabase of known sequences are frequently calculated using an heuristicapproach, as described in Altschul et al. (1994) Nat. Genet. 6:119.

[0013] Alternatively, “reverse genetics” is used to identify genefunction. Techniques include the use of genetically modified cells andanimals. A targeted gene may be “knocked out” by site specificrecombination, introduction of anti-sense constructs or constructsencoding dominant negative mutations, and the like (see, for someexamples, U.S. Pat. No. 5,631,153, Capecchi et al. for methods ofcreating transgenic animals; Lagna et al. (1998) Curr Top Dev Biol36:75-98 for an overview of the use of dominant negative constructs; andNellen et al. (1993) Trends Biochem Sci 18(11):419-23 for a review ofanti-sense constructs).

[0014] Cells and animals may also be modified by the introduction ofgenetic function, through the introduction of functional codingsequences corresponding to the genetic sequence of interest. Generaltechniques for the creation of transgenic animals may be found in MouseGenetics and Transgenics: A Practical Approach (Practical ApproachSeries) by Ian J. Jackson (Editor), Catherine M. Abbott (Editor). Whilethey have proven useful in many ways, however, transgenic animalsfrequently suffer from problems of time and expense, as well ascompensatory mechanisms, redundancies, pleiotropic genetic effects, andthe lethality of certain mutations.

[0015] Another approach for discovering the function of genes utilizesgene chips or microarrays. DNA sequences representing all the genes inan organism can be placed on miniature solid supports and used ashybridization substrates to quantitate the expression of all the genesrepresented in a complex mRNA sample, and assess the effect of aperturbation on gene expression. Methods utilizing genetic sequencemicroarrays can be applied to pharmaceutical target validation. In thesemethods, genetic modifications are evaluated for their effects on theexpression of particular genes. A few examples include U.S. Pat. No.6,013,437; Luria et al., “Method for identifying translationallyregulated genes”; U.S. Pat. No. 6,004,755, Wang, “Quantitativemicroarray hybridization assays”; and U.S. Pat. No. 5,994,076, Chenchiket al., “Methods of assaying differential expression”.

[0016] Gene reporter assays can also be used to characterize the effectof genetic modifications by their ability to inhibit the expression ofspecific genes in gene reporter assays. For example, Ashby et al. U.S.Pat. No. 5,569,588; Rine and Ashby U.S. Pat. No. 5,777,888 describe agenome reporter matrix approach for comparing the effect of drugs on apanel of reporter genes to reveal effects of a compound on thetranscription of a spectrum of genes in the genome.

SUMMARY OF THE INVENTION

[0017] Methods and compositions are provided for function homologyscreening by discriminating between different cellular pathways, both asto the effect of genotype modification on cellular pathways and changesin parameters resulting from changes in the pathways, and using thediscrimination for determining the effect of an agent on a mammaliancell culture system simulating cellular functions, as in a cellularstate of interest, usually associated with a diseased state of amammalian host. Cells capable of responding to factors and simulatingthe state of interest are employed, where the factors enhance theresponse of the measured components of the phenotype to approximate theresponse in vivo to external agents. A sufficient number of factors areemployed to involve a plurality of pathways and a sufficient number ofparameters are selected to be involved with a plurality of pathways andprovide a robust response to the effect of a change in the environmentof the cells. A flexible, multiplex screening assay is provided forscreening and biological activity classification of biologically activeagents. Assays are performed in the presence of an agent of interest,whereby a level of at least about 3 markers is obtained associated withthe presence of the agent and the results compared to the level of themarkers observed in the absence of the agent. By employing reagents thatare known to have an effect on a pathway in conjunction with the agent,the pathway affected by the agent can be determined. The data resultingfrom the assays can be processed to provide robust comparisons betweendifferent environments and agents. Databases are provided so that agentsand their effects may be compared. Particularly, biomaps are providedallowing for ready comparison,—visual, mathematical and electronic—ofthe results of different assays involving the same or different agentswith assays involving the same or different reagents.

BRIEF DESCRIPTION OF THE DRAWINGS

[0018]FIG. 1. Assay combinations for screening inflammatory modulators.A. Expression of selected readout parameters on selected assaycombinations of HUVEC treated with proinflammatory cytokines. Confluentcultures of HUVEC cells were treated with TNF-α (5 ng/ml), IFN-γ (100ng/ml) or IL-1 (1 ng/ml). After 24 hours, cultures were washed andevaluated for the presence of the parameters ICAM-1 (1), VCAM-1 (2),E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7) by cell-basedELISA. For this, plates were inverted until dry, blocked with 1% Blottofor 1 hr, and treated with primary antibodies (obtained from Pharmingenand Becton Dickinson) at 1 ng/ml for 1 hr. Plates were washed andsecondary peroxidase-conjugated anti-mouse IgG antibody (Promega) at1:2500 was applied for 1 hr. After washing, TMB substrate (Kierkegaard &Perry) was added and color developed. Development was stopped byaddition of H₂SO₄ and the absorbance at 450 nm (subtracting thebackground absorbance at 650 nm) with a Molecular Devices plate reader.The relative expression levels of each parameter are indicated by the ODat 450 nm shown along the y-axis. The mean +/−SD from triplicate samplesis shown. B. Expression of selected readout parameters on selected assaycombinations of HUVEC treated with cytokine combinations. Confluentcultures of HUVEC cells were treated with TNF-α (5 ng/ml), IFN-γ (100ng/ml) or TNF-α and IFN-γ. After 24 hours, cultures were washed andevaluated for the presence of the parameters ICAM-1 (1), VCAM-1 (2),E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7) by cell-basedELISA performed as described above. The relative expression levels ofeach parameter are indicated by the OD at 450 nm. The mean +/−SD fromtriplicate samples are shown. C. Expression of selected readoutparameters on selected assay combinations of HUVEC treated with cytokinecombinations. Confluent cultures of HUVEC cells were treated with TNF-α(5 ng/ml)+IFN-γ (100 ng/ml) or TNF-α (5 ng/ml)+IFN-γ (100 ng/ml)+IL-1 (1ng/ml). After 24 hours, cultures were washed and evaluated for thepresence of the parameters ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8(4), CD31 (5), HLA-DR (6) and MIG (7) by cell-based ELISA performed asdescribed above. The relative expression levels of each parameter areindicated by the OD at 450 nm. The mean +/−SD from triplicate samplesare shown. * indicates p<0.05 comparing results obtained with the twoseparate conditions, n=3.

[0019]FIG. 2. Assay combinations for screening inflammatory modulators.Confluent cultures of HU VEC cells were treated with combinations ofTNF-α (5 ng/ml), IFN-γ (200 ng/ml) and IL-1 (1 ng/ml) or base media.After 24 hours, cultures were washed and evaluated for the presence ofICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6)and MIG (7) by cell-based ELISA performed as described in FIG. 1. A. Therelative expression level of each parameter is shown along the y-axis asaverage value of the OD measured at 450 nm of triplicate samples. B. Acolor-coded representation of the data shown in A. For each parameterand assay combination, the square is colored light gray if the parametermeasurement is unchanged (<20% above or below the measurement in thefirst assay combination (IL-1+TNF+IFN-γ) or p>0.05, n=3); white/grayhatched indicates that the parameter measurement is moderately increased(>20% but <50%); white indicates the parameter measurement is stronglyincreased (>50%); black/gray hatched indicates that the parametermeasurement is moderated decreased (>20% but <50%); black indicates thatthe parameter measurement is strongly decreased (>50% less than thelevel measured in the first assay combination). C. A tree diagramrepresentation of the biomaps prepared from data shown in A and B.Resulting biomaps were compared and analyzed by hierarchical clustering.Biomap relationships are visualized by a tree diagram in which a) eachterminal branch point represents the biomap prepared from the indicatedassay combination; b) the length of the vertical distance from the upperhorizontal line (no change and control patterns) to the termini arerelated to the extent of difference in the readout pattern from thereference pattern (IL-1+TNF-α+IFN-γ); and c) the distance along thebranches from one terminal pattern value to another reflects the extentof difference between them.

[0020]FIG. 3. Effect of neutralizing anti-TNF-α antibody on theexpression of readout parameters in the inflammatory assay combinationcontaining three factors (IL-1+TNF-α+IFN-γ). Confluent cultures of HUVECcells were treated with TNF-α (5 ng/ml)+IFN-γ (200 ng/ml)+IL-1 (1 ng/ml)in the presence or absence of neutralizing anti-TNF-α (R&D Systems) orcontrol Goat anti-IgG. After 24 hours, cultures were washed andevaluated for the cell surface expression of ICAM-1 (1), VCAM-1 (2),E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7) by cell-basedELISA performed as described in FIG. 1. A. The relative expression ofeach parameter is shown along the y-axis as average value of the ODmeasured at 450 nm of triplicate samples. The mean +/−SD from triplicatesamples are shown. * indicates p<0.05 comparing results obtained withanti-TNF-α to the control. B. A color-coded representation of biomapsprepared from the data shown in A. For each parameter and assaycombination, the square is colored light gray if the parametermeasurement is unchanged (<20% above or below the measurement in thefirst assay combination (IL-1+TNF-α+IFN-γ) or p>0.05, n=3); white/grayhatched indicates that the parameter measurement is moderately increased(>20% but <50%); white indicates the parameter measurement is stronglyincreased (>50%); black/gray hatched indicates that the parametermeasurement is moderated decreased (>20% but <50%); black indicates thatthe parameter measurement is strongly decreased (>50% less than thelevel measured in the first assay combination).

[0021]FIG. 4. A and B. Effect of NFκB inhibitors nordihydroguaiareticacid (NHGA) and pyrrolidine dithiocarbamate (PDTC), MAP kinase inhibitorPD098059, or ibuprofen on the expression of readout parameters in theinflammatory assay combination containing three factors(IL-1+TNF-α+IFN-γ). Confluent cultures of HUVEC cells were treated withTNF-α (5 ng/ml)+IFN-γ (200 ng/ml)+IL-1 (20 ng/ml) in the presence orabsence of (A) 10 μM NHGA, 200 μM PDTC or 9 μM PD098059; (B) 125-500 μMibuprofen. Compounds were tested at the highest concentration at whichthey were soluble, and/or did not result in loss of cells from theplate. After 24 hours, cultures were washed and evaluated for the cellsurface expression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4),CD31 (5), HLA-DR (6) and MIG (7) by cell-based ELISA performed asdescribed in FIG. 1. A color-coded representation of the biomapsprepared from the data is shown. For each parameter and assaycombination, the square is colored light gray if the parametermeasurement is unchanged (<20% above or below the measurement in thefirst assay combination (IL-1+TNF-α+IFN-γ), or p>0.05, n=3); white/grayhatched indicates that the parameter measurement is moderately increased(>20% but <50%); white indicates the parameter measurement is stronglyincreased (>50%); black/gray hatched indicates that the parametermeasurement is moderated decreased (>20% but <50%); black indicates thatthe parameter measurement is strongly decreased (>50% less than thelevel measured in the first assay combination).

[0022]FIG. 4C. Effect of compounds on the reference readout pattern inthe inflammatory assay combination containing three factors(IL-1+TNF-α+IFN-γ). Confluent cultures of HUVEC cells were treated withTNF-α (5 ng/ml)+IFN-γ (200 ng/ml)+IL-1 (1 ng/ml) in the presence orabsence of compounds or agents as listed in Table 1. After 24 hours,cultures were washed and evaluated for the cell surface expression ofparameters of ICAM-1, VCAM-1, E-selectin, IL-8, CD31, HLA-DR and MIG bycell-based ELISA performed as described in FIG. 1. The resulting biomapswere compared (Table 1) and analyzed by hierarchical clustering. Biomaprelationships are visualized by a tree diagram in which a) each terminalbranch point represents the biomap prepared from the indicated assaycombination; b) the length of the vertical distance from the upperhorizontal line (no change and control patterns) to the termini arerelated to the extent of difference in the readout pattern from thereference pattern (IL-1+TNF-α+IFN-γ); and c) the distance along thebranches from one terminal pattern value to another reflects the extentof difference between them. Similar patterns are thus clusteredtogether. The figure illustrates the reproducibility of patternsresulting from treatment with a single drug in multiple experiments, andthose resulting from multiple drugs that target the same signalingpathway.

[0023]FIG. 5. Effect of neutralizing anti-TNF-α antibody or NFκBinhibitors AA861 and nordihydroguaiaretic acid (NHGA) on readoutpatterns in multiple assay combinations. Confluent cultures of HUVECcells were treated with TNF-α (5 ng/ml), IFN-γ (200 ng/ml), IL-1 (1ng/ml), the combination of TNF-α+IFN-γ+IL-1, or media in the presence orabsence of 5 μg/ml neutralizing anti-TNF-α (R&D Systems), 20 μM M861 or10 μM NHGA. After 24 hours, cultures were washed and evaluated for thecell surface expression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8(4), and MIG (5) by cell-based ELISA performed as described in FIG. 1. Acolor-coded representation of the biomaps prepared from the data isshown, coded as described in FIG. 2B.

[0024]FIG. 6. Effect of a neutralizing anti-TNF-α antibody on readoutpatterns in multiple assay combinations. Confluent cultures of HUVECcells were treated with TNF-α (5 ng/ml), IL-1 (1 ng/ml), an activatingantibody against the TNF-α-receptor p55, (Act-anti-p55, 3 μg/ml, R&DSystems), or media in the presence or absence of neutralizing TNF-αantibody (Anti-TNF-α, 5 μg/ml, R&D Systems). After 24 hours, cultureswere washed and evaluated for the cell surface expression of ICAM-1 (1),VCAM-1 (2), E-selectin (3), CD31 (4), and MIG (5) by cell-based ELISAperformed as described in FIG. 1. A color-coded representation of thebiomaps prepared from the data is shown, coded as described in FIG. 2B.

[0025]FIG. 7. Effect of soluble TNF-α-receptor p55-Fc fusion protein(p55-Fc) on the expression of readout parameters in multiple assaycombinations. A. Confluent cultures of HUVEC cells were treated withTNF-α (5 ng/ml)+IFN-γ (100 ng/ml)+IL-1 (1 ng/ml) in the presence orabsence of p55-Fc (50 ng/ml, Pharmingen). After 24 hours, cultures werewashed and evaluated for the cell surface expression of ICAM-1 (1),VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7)by cell-based ELISA performed as described in FIG. 1. The relativeexpression of each parameter is shown along the y-axis as average valueof the OD measured at 450 nm of triplicate samples. The mean +/−SD fromtriplicate samples are shown. * indicates p<0.05 comparing resultsobtained with anti-TNF-α to the control. B. Confluent cultures of HUVECcells were treated with TNF-α (5 ng/ml), IFN-γ (100 ng/ml), IL-1 (1ng/ml), the combination of TNF-α+IFN—Y+IL-1, or media in the presence orabsence of p55-Fc (50 ng/ml, Pharmingen). After 24 hours, cultures werewashed and evaluated for the cell surface expression of ICAM-1 (1),VCAM-1 (2), E-selectin (3), IL-8 (4), and MIG (5) by cell-based ELISAperformed as described in FIG. 1. A color-coded representation of thebiomaps prepared from the data is shown, coded as described in FIG. 2B.C. Confluent cultures of HUVEC cells were treated with TNF-α (5 ng/ml),IL-1 (1 ng/ml), an activating antibody against the TNF-α-receptor p55 (5μg/ml, Pharmingen), or media with or without p55-Fc (50 ng/ml). After 24hours, cultures were washed and evaluated for the cell surfaceexpression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), CD31 (4), and MIG(5) by cell-based ELISA performed as described in FIG. 1. A color-codedrepresentation of the biomaps prepared from the data is shown, coded asdescribed in FIG. 2B.

[0026]FIG. 8. Effect of an activating antibody against TNF-α-receptorp55 (Act-anti-p55) on readout patterns in multiple assay combinations.Confluent cultures of HUVEC cells were treated with TNF-α (5 ng/ml),IFN-γ (100 ng/ml), IL-1 (1 ng/ml), the combination of TNF-α+IFN-γ+IL-1,or media in the presence or absence of Act-anti-p55 (Act-anti-p55, 3μg/ml, R&D Systems). After 24 hours, cultures were washed and evaluatedfor the cell surface expression of ICAM-1 (1), VCAM-1 (2), E-selectin(3), IL-8 (4), and MIG (5) by cell-based ELISA performed as described inFIG. 1. A color-coded representation of the biomaps prepared from thedata is shown, coded as described in FIG. 2B.

[0027]FIG. 9. Effect of a soluble TNF-α-receptor p55-Fc fusion protein(p55-Fc) on the expression of readout parameters in an assay combinationcontaining an activating antibody against TNF-α-receptor p55(Act-anti-p55). Confluent cultures of HUVEC cells were treated with orwithout (Control) Act-anti-p55 in the presence or absence of p55-Fc.After 24 hours, cultures were washed and evaluated for the cell surfaceexpression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31(5), HLA-DR (6) and MIG (7) by cell-based ELISA performed as describedin FIG. 1. The relative expression of each parameter is shown along they-axis as average value of the OD measured at 450 nm of triplicatesamples. The mean +/−SD from triplicate samples are shown. * indicatesp<0.05 comparing results obtained with Act-anti-p55 orAct-anti-p55+p55-Fc to the Control, n=3.

[0028]FIG. 10. Effect of neutralizing antibodies against IL-1 or TNF-αon the expression of readout parameters in the optimized assaycombination of Example 1. Confluent cultures of HUVEC cells were treatedwith TNF-α (5 ng/ml)+IFN-γ (100 ng/ml)+IL-1 (1 ng/ml) in the presence orabsence of neutralizing antibodies to IL-1 (Anti-IL-1, 4 μg/ml, R&DSystems), TNF-α (Anti-TNF-α, μg/ml/ml, R&D Systems) or the combination.After 24 hours, cultures were washed and evaluated for the cell surfaceexpression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31(5), HLA-DR (6) and MIG (7) by cell-based ELISA performed as describedin FIG. 1. A. The relative expression of each parameter is shown alongthe y-axis as average value of the OD measured at 450 nm of triplicatesamples. The mean +/−SD from triplicate samples are shown. B. Acolor-coded representation of the biomaps prepared from the data in FIG.12A is shown, coded as described in FIG. 2B where the control conditionincludes TNF-α+IFN-γ+IL-1.

[0029] FIGS. 11A-B. Effect of AG126 and PPM-18 on expression of readoutparameters in the optimized assay combination of Example 1. Confluentcultures of HUVEC cells were treated with TNF-α (5 ng/ml)+IFN-γ (100ng/ml)+IL-1 (1 ng/ml) in the presence or absence of AG126 (25 μM) orPPM-18 (2 μM) or the combination. Compounds were tested at the highestconcentration at which they were soluble, and/or did not result in celldeadhesion. After 24 hours, cultures were washed and evaluated for thecell surface expression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8(4), CD31 (5), HLA-DR (6) and MIG (7) by cell-based ELISA performed asdescribed in FIG. 1. A color-coded representation of the biomapsprepared from the data is shown in 11B, coded as described in FIG. 2B.

[0030]FIG. 12. Confluent cultures of HUVEC cells were treated withcombinations of IL-4 (20 ng/ml), TNF-α (5 ng/ml), histamine (HIS, 10 μM)and/or base media. After 24 hours, cultures were washed and evaluatedfor the presence of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4),CD31 (5), P-selectin (6) and Eotaxin-3 (7) by cell-based ELISA performedas described in FIG. 1. A color-coded representation of the biomapsprepared from the data is shown, coded as described in FIG. 2B. For eachparameter and assay combination, the square is colored light gray if theparameter measurement is unchanged (<20% above or below the measurementin the first assay combination (IL-4+TNF-α+HIS) or p>0.05, n=3);white/gray hatched indicates that the parameter measurement ismoderately increased (>20% but <50%); white indicates the parametermeasurement is strongly increased (>50%); black/gray hatched indicatesthat the parameter measurement is moderated decreased (>20% but <50%);black indicates that the parameter measurement is strongly decreased(>50% less than the level measured in the first assay combination).

[0031]FIG. 13. Cultures of normal human epithelial keratinocytes (NHEK)were treated with combinations of TNF-α (50 ng/ml), IFN-γ (50 ng/ml),IL-1 (1 ng/ml) and or base media. After 48 hours, cultures were washedand evaluated for the presence of MIG (1), ICAM-1 (2), CD44 (3), IL-8(4), MIP-3alpha (5), MCP-1 (6), and E-cadherin (7) by cell-based ELISAperformed as described in FIG. 1. A color-coded representation of thebiomaps prepared from the data is shown, coded as described in FIG. 2B.For each parameter and assay combination, the square is colored lightgray if the parameter measurement is unchanged (<20% above or below themeasurement in the first assay combination (IL-1+IFN-γ) or p>0.05, n=3);white/gray hatched indicates that the parameter measurement ismoderately increased (>20% but <50%); white indicates the parametermeasurement is strongly increased (>50%); black/gray hatched indicatesthat the parameter measurement is moderated decreased (>20% but <50%);black indicates that the parameter measurement is strongly decreased(>50% less than the level measured in the first assay combination).

[0032]FIG. 14. Assay combinations containing HUVEC and T cellco-cultures. Confluent cultures of HUVEC were incubated with media (NoCells), TNF-α, (5 ng/ml), IFN-γ (100 ng/ml) or KIT255 T cells with andwithout IL-2 (10 ng/ml) and/or IL-12 (10 ng/ml). After 24 hours cultureswere washed and evaluated for the cell surface expression of ICAM-1 (1),VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7)by cell-based ELISA performed as described in FIG. 1. The relativeexpression of each parameter is shown along the y-axis as average valueof the OD measured at 450 nm.

[0033]FIG. 15. Schematic representation of retroviral vector constructs(not drawn to scale). LTR, long terminal repeat; IRES, internalribosomal entry site.

[0034]FIG. 16. Effect of Bcl-3 gene over-expression on readout patternsin multiple BioMap systems of inflammation. HUVEC cells were transducedwith either Bcl-3-expressing retroviral vector (Bcl-3) or control emptyvector (control). Confluent cultures were treated with either TNF-α (5ng/ml), IL-1 (1 ng/ml), TNF-α (5 ng/ml)+IFN-γ (100 ng/ml)+IL-1 (1ng/ml), or media only (no cytokine). After 24 hours, cultures werewashed and evaluated for the cell surface expression of ICAM-1 (1),VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7)by cell-based ELISA performed as described in FIG. 1. A color-codedrepresentation of the biomaps prepared from the data is shown, coded asdescribed in FIG. 2B.

[0035]FIG. 17. Effect of over-expression of bcl-2 and bcl-xl proteins ona panel of assay combinations. HUVEC cells were transduced with eitherBcl-2, Bcl-xL or control empty vector (control). Confluent cultures weretreated with either ceramide (10 μm), TNF-α (5 ng/ml), ceramide (10μm)+TNF-α (5 ng/ml), or media only. After 24 hours, cells were washedand evaluated for the surface expression of ICAM-1 (1), VCAM-1 (2), andMIG (3) by cell-based ELISA performed as described in FIG. 1. Cellsupernatants were collected and analyzed for the presence of lactatedehydrogenase LDH (4) by CytoTox96 assay (Promega). The level of LDH inculture supernatants from cells treated with TNF-α or ceramide+TNF-αwasincreased 2-fold and 2.2-fold, respectively, over the levels measured inuntreated or ceramide-treated cells. A color-coded representation of thebiomaps prepared from the data is shown, coded as described in FIG. 2B.

[0036]FIG. 18. Effect of TNF-R1-p55 antisense oligonucleotide onmultiple assay combinations. Confluent cultures of HUVEC cells weretransfected with TNF-R1 antisense or control β-globin antisenseoligonucleotides, and then treated with either TNF-α (0.5 ng/ml), orIL-1 (1 ng/ml). After 4 hours, cells were harvested and evaluated forthe cell surface expression of ICAM-1 (1), VCAM-1 (2), E-selectin (3),and CD31 (4) by flow cytometry. Flow cytometry was performed aspreviously described (Berg, Blood, 85:31, 1995). A color-codedrepresentation of the biomaps prepared from the data is shown, coded asdescribed in FIG. 2B.

DESCRIPTION OF THE SPECIFIC EMBODIMENTS

[0037] Flexible multiplex screening assays are provided for thescreening and biological activity classification of biologically activeagents and genes.

[0038] In the screening assays for the biologically active agents, theeffect of altering the environment of cells in culture is tested with apanel of cells and cellular environments. The effect of the altering ofthe environment is assessed by monitoring multiple output parameters.The result is an analysis providing “function homology,” wherecomparison of two different environments, particularly differing bydifferent compounds present in the environment, can be directly comparedas to their similarities and differences. By being able to compare theeffect on a family of parameters as to the degree of change in theabsence of the compounds, the function of the compounds can be compared,the pathways affected identified and side effects predicted.

[0039] In the screening assays for genetic agents, polynucleotides areadded to one or more of the cells in a panel in order to alter thegenetic composition of the cell. The output parameters are monitored todetermine whether there is a change in phenotype affecting particularpathways. In this way, genetic sequences are identified that encode oraffect expression of proteins in pathways of interest, particularlypathways associated with aberrant physiological states.

[0040] Assay combinations, usually employing cell cultures, are providedthat simulate physiological cell states of interest, particularlyphysiological cell states in vivo, usually using the same type of cellsor combinations of cells. These cell cultures are created by theaddition of a sufficient number of different factors to provoke aresponse that simulates cellular physiology of the state of interest andto allow for the status of cells in culture to be determined in relationto a change in an environment. The state of interest will normallyinvolve a plurality of pathways where the pathways regulate a pluralityof parameters or markers identifying a phenotype associated with thestate of interest.

[0041] The phenotype can be generated by including a plurality offactors that induce pathways affecting the production of the phenotypeby the up or down regulation of formation of the parameters asdetectable products or may be based on the nature of the cell, e.g.neoplastic primary cells, cell lines, etc., where the factors enhancethe response of the cells in vitro to more closely approximate theresponse of interest. The factors are naturally occurring compounds,e.g. known compounds that have surface membrane receptors and induce acellular signal that results in a modified phenotype, or syntheticcompounds that mimic the naturally occurring factors. In some instances,the factors will act intracellularly by passing through the cell surfacemembrane and entering the cytosol with binding to components in thecytosol, nucleus or other organelle. In providing the environment by useof the factors or mimetics, one provides the activities of the factorsto the environment, using the naturally occurring factors or theirmimetics. In referring to factors, it is understood that it is theactivities of the factors that are of interest and not necessarily aparticular naturally occurring factor itself.

[0042] The nature and number of parameters measured generally reflectsthe response of a plurality of pathways. The subject approach providesfor robust results having enhanced predictability in relation to thephysiological state of interest. The results may be compared to thebasal condition and/or the condition in the presence of one or more ofthe factors, particularly in comparison to all of the factors used inthe presence and absence of agent. The effects of different environmentsare conveniently provided in biomaps, where the results can bemathematically compared.

[0043] For screening assays with genetic agents, the same approach willbe used as above. The genetic agents are added to cells, which areplaced in a medium where one or more factors may be present to provide adesired environment, namely an environment of interest, such as aphysiological environment involved with an aberrant, e.g. diseased,state. Parameters associated with the pathways related to thephysiological state are monitored. Where the parameters show a patternindicating the up or down regulation of a pathway, the genetic agent isdeduced to encode or affect the expression of a member of the pathway.In this way one can determine the role a gene plays in the physiologicalstate of interest, as well as define targets for therapeuticapplication.

[0044] Once biomaps have been prepared for pathways and/or environmentsof interest, assays may be carried out with or without the factors.Knowing the variation in parameters with individual factors anddifferent combinations of factors, one can compare the effect of anagent on a cell culture by measuring parameters that have beenpreviously measured in different assay combinations. The observed effectof the agent on the levels of the different parameters may then becorrelated with the observed effect of the factors and combinations offactors in the biomap dataset.

[0045] Numerous factors are known that induce pathways in cells that areresponsive to the factor. For the most part, factors bind to cellsurface receptors, although other receptors may be involved, such asreceptors at the nuclear membrane. In addition, where a factor is ableto penetrate the surface membrane, through passive or active transportor through endocytosis, the factor may bind to components of themembrane, cytosol or an organelle, e.g. nucleus. It has now been foundthat by using a combination of multiple factors to provoke a cellularresponse, and multiple parameters associated with a physiological stateof interest, one can investigate multiple individual cellularphysiological pathways and simulate the physiological response to achange in environment and obtain greater predictability as to the waythe physiological situation will respond to the change in environment.The subject screening of physiologically active compounds provides forgreater assurance of the effect of the change of environment in thephysiological circumstances in which the change is to occur.

[0046] Multiple factors are employed, which provides a robust simulationof the physiological state or physiologic pathways of interest andallows for reliable responses that can be correlated with in vivocellular responses. Alternatively, factors can be employed that simulatethe environment of the cells in vivo (particularly a living animal, butmay be cells, tissue, organelles, etc.), so that the cell physiology ofthe cells in culture more closely approximates the cell physiology invivo.

[0047] Combinations of factors are employed where pathways involved witha particular cellular status are active, resulting in the modulation ofthe formation of various products, such as RNA, e.g. mRNA, tRNA, etc.,proteins, metabolites, functional states of proteins, etc., wheredifferent products are associated with different pathways. All of theseproducts are detectable and can be analyzed by appropriate assays.Specific products are selected for measurement, usually avoidingproducts that give redundant information, e.g. that are commonlyregulated. The results obtained from individual assay combinations maythen be compiled. These results are compared or normalized with thecontrol state, which can be the cells in an appropriate medium with orwithout exogenous factors other than the test agent, or the stimulatedculture, which is the cells in the absence of the agent, but in samemedium with the factors that induce the cells in culture to simulatecells in a complex environment that occurs in vivo. For the most part,the control state will be the cell culture with the same factors andmeasuring the same parameters as the test state comprising the agent.

[0048] In referring to simulation to a physiological state, thesimulation will usually include at least three different regulatedfeatures (parameters) shared with in vivo cell counterparts in normal ordiseased states. Alternatively, the simulation may include a cellculture system that allows discrimination of modifications in at leastthree different signaling pathways or cell functions operative in vivounder conditions of interest.

[0049] The results can be entered into a data processor to provide abiomap dataset. Algorithms are used for the comparison and analysis ofbiomaps obtained under different conditions. The effect of factors andagents is read out by determining changes in multiple parameters in thebiomap. The biomap will include the results from assay combinations withthe agent(s), and may also include one or more of the control state, thesimulated state, and the results from other assay combinations usingother agents or performed under other conditions. For rapid and easycomparisons, the results may be presented visually in a graph of abiomap, and can include numbers, graphs, color representations, etc.

BIOMAP

[0050] The biomap is prepared from values obtained by measuringparameters or markers of the cells in the presence and absence ofdifferent factors, as well as comparing the presence of the agent ofinterest and at least one other state, usually the control state, whichmay include the state without agent or with a different agent. Theparameters include cellular products or epitopes thereof, as well asfunctional states, whose levels vary in the presence of the factors.Desirably, the results are normalized against a standard, usually a“control value or state,” to provide a normalized data set. Valuesobtained from test conditions can be normalized by subtracting theunstimulated control values from the test values, and dividing thecorrected test value by the corrected stimulated control value. Othermethods of normalization can also be used; and the logarithm or otherderivative of measured values or ratio of test to stimulated or othercontrol values may be used. Data is normalized to control data on thesame cell type under control conditions, but a biomap may comprisenormalized data from one, two or multiple cell types and assayconditions.

[0051] By referring to a biomap is intended that the dataset willcomprise values of the levels of at least two sets of parametersobtained under different assay combinations. Depending on the use of thebiomap, the biomap may also include the parameter values for each thefactors included in the assay combination, individually and/or togetherwith fewer than the entire assay combination. Compilations of biomapsare developed that provide the values for a sufficient number ofalternative assay combinations to allow comparison of values obtainedwhere factors have not been added. While such an assay can be lesspredictive of in vivo conditions, in many situations it can suffice toprovide a rapid, inexpensive screen providing useful data. For example,if one were interested in side effects of a candidate compound, by usinga cell culture that is in a basal state, one could evaluate whether thecandidate compound produced an aberrant state, e.g. normal as comparedto inflamed. The parameter values are usually created electronically andstored in a data processor for comparison with other biomaps anddatabases compiled from the biomaps.

[0052] A graph of a biomap can be presented visually as numericalvalues, symbols, color gradations, or the like, indicating the parametervalues. The graph is conveniently presented where color and/or designprovide an indication of the level of the particular marker. Theindicators may be vertical or horizontal as to the individual markersand the assay combinations, so that by looking at the graph, one canimmediately compare the levels of the different markers for each of thecombinations and discern patterns related to the assay combinations andthe differences between assay combinations. In this way, one can rapidlyrelate different candidate pharmacologic agents, the pathways theyaffect and their efficacy in modulating the individual pathways.

[0053] Optionally, a biomap can be annotated to indicate informationabout the sources of information for the dataset. Annotations mayinclude, for example, the number of assay conditions in a panel (n);controls used for normalization (N); parameters (P), which may bedesignated for the number and identity of the parameters; environmentalchanges, such as the addition of factors and/or agents or a change inthe physical conditions (V); cell type (C); and the like. The annotationmay further specify specific factors or conditions present in one of theassay combinations, e.g. n1, n2, n3, etc., where the presence of factorsin the assay combination is designated (F), temperature may bedesignated (T), pH, etc. The parameters may also be designated in thisas, e.g. P1=ICAM-1, P2=VCAM-1, P3=E-selectin, etc. Written out, theannotation may be set forth as: (v) B {n; N; P; C; F}.

[0054] As an example: a biomap is produced from monitoring endothelialcells for four parameters in four assay combinations. The assaycombinations include a basal control, a stimulated control, and acontrol where the pathway of interest is blocked by the addition ofneutralizing antibody. The compound being tested is an NSAID. The biomap(B) may be annotated as:

(NSAID) B {n=14; N=basal/stim.; P=1-4; C=endothelial; F_((n4))=neut. Ab}

[0055] A database of biomaps can be compiled from sets of experiments,for example, a database can contain biomaps obtained from a panel ofassay combinations, with multiple different environmental changes, whereeach change can be a series of related compounds, or compoundsrepresenting different classes of molecules. In another embodiment, adatabase comprises biomaps from one compound, with multiple differentcell panels.

[0056] Mathematical systems can be used to compare biomaps, and toprovide quantitative measures of similarities and differences betweenthem. For example, the biomaps in the database can be analyzed bypattern recognition algorithms or clustering methods (e.g. hierarchicalor k-means clustering, etc.) that use statistical analysis (correlationcoefficients, etc.) to quantify relatedness of biomaps. These methodscan be modified (by weighting, employing classification strategies,etc.) to optimize the ability of a biomap to discriminate differentfunctional effects. For example, individual parameters can be given moreor less weight when analyzing the dataset of the biomap, in order toenhance the discriminatory ability of the biomap. The effect of alteringthe weights assigned each parameter is assessed, and an iterativeprocess is used to optimize pathway or cellular function discrimination.

ASSAY C OMBINATION

[0057] Cells for use in the assays of the invention can be an organism,a single cell type derived from an organism, or can be a mixture of celltypes, as is typical of in vivo situations, but may be the differentcells present in a specific environment, e.g. vessel tissue, liver,spleen, heart muscle, brain tissue, etc. The cells will usually be ofthe same type as the cells of the physiologic conditions, sharing atleast a partially common phenotype. For example, both the culture andthe in vivo physiologic condition could involve T-lymphocytes, where theculture would involve a T-lymphocyte cell line or primary T-lymphocyte.In some instances the cells in the culture or assay combination may besubstantially different from the cells of the physiologic state ofinterest. Where it is known or can be shown that the pathways of thecells in culture are paradigmatic of the pathways of the cells ofinterest, the cells in culture may be selected for reasons ofconvenience, that a body of data has been built up with these cells,easy growth and maintenance, the use by others allowing for moreaccurate comparisons of the results, etc.

[0058] Of particular interest are primary cells that can be used in aculture, where the primary cells of interest are, in effect,synchronized in their phenotype, by the use of the factors. When thecells are not in synchrony, an average value will be obtained. Theculture conditions will include the presence of factors that provide forthe desired physiologic state, including the desired phenotype, but mayalso be varied, for example, as to temperature, pH, presence of othercell types, and the like. Each combination of cell(s) and cultureconditions provides one “assay combination”, which will generate a setof parameter readouts. In a typical screen, a panel of one or more assaycombinations is used for each compound to be tested. For each assaycombination, a set of parameter readouts will be obtained in thepresence of an agent that is being tested. These readouts will becompared to readouts of an assay combination lacking the agent, whichmay be performed contemporaneously or may be performed at another time,either before or after the assay combination with the agent of interest.As indicated above, the comparison may be with the same type of cells inthe absence of the factors, in the presence of the factors, or multiplestimulating or inhibiting factors or in the presence of a differentagent or other condition that serves to provide a meaningful comparison.

[0059] Single cell types are of interest for many screeningapplications, and in individual assay combinations will be provided withfactors that induce the desired phenotype. The factors may be theproducts of other cell types, for example, expressed proteins associatedwith a disease, may be compounds that simulate naturally occurringfactors, may be surface membrane proteins free of the membrane or aspart of microsomes, or other reagent that induces the appropriatepathway to aid in the simulation of the phenotype or provides theappropriate environment to simulate the physiological condition. Thefactors (including mimetics thereof) may be added individually or incombination, from feeder cells, may be added as a bolus or continuously,where the factor is degraded by the culture, etc. Illustrative naturallyoccurring factors include cytokines, soluble receptors, hormones,prostaglandins, steroids, etc, that may be isolated from natural sourcesor produced by recombinant technology or synthesis, compounds that mimicthe action of other compounds or cell types, e.g. an antibody which actslike a factor or mimics a factor, such as synthetic drugs that act asligands for target receptors. For example, in the case of the T cellreceptor, the action of an oligopeptide processed from an antigen andpresented by an antigen-presenting cell, etc. can be employed. Where afamily of related factors are referred to with a single designation,e.g. IL-1, VEGF, IFN, etc., in referring to the single description, anyone or some or all of the members of the group are intended, where theliterature will be aware of how the factors are to be used in thecontext of the assay combination.

[0060] The assay combinations find use in investigating complex statesof cells, frequently resulting from cellular interactions, which mayfrequently involve at least about two, frequently three, or moredifferent cell types and/or will involve a plurality of soluble factorsthat are present in a physiological fluid, particularly as the result ofa physiological event, e.g. infection, neoplasia, autoimmune, etc. thatis, frequently involving more than one cell type and more than onefactor. The measured parameters may be obtained from one or more of thecell types. The cells in the assay combination, either one or up to eachof the different cell types, can have identifying characteristicsallowing them to be distinguished during analysis. Various techniquesmay be employed to identify the cells in the assay combination foranalysis of the parameters of interest.

[0061] Conditions of interest include inflammatory processes that occurin response to infection, trauma, etc., autoimmune diseases, such asdiabetes, lupus, arthritis, etc., cardiovascular diseases, such asstroke, atherosclerosis, etc., neoplasia, hyperplasia, addiction,infection, obesity, cellular degeneration, apoptosis, senescence,differentiation, and the like.

[0062] Multifactorial, usually involving multicellular, assaycombinations, may reflect many of the conditions indicated above, suchas inflammatory processes; autoimmune diseases; cardiovascular diseases;tumors, etc. That is, a multiplicity of factors are employed toinfluence a plurality of cellular pathways and a multiplicity ofparameters are measured that reflect the status of the pathways.Degenerative diseases, including affected tissues and surrounding areas,may be exploited to determine both the response of the affected tissue,and the interactions with other cell types or other parts of the body.

[0063] The invention is suitable for use with any cell type, includingprimary cells, normal and transformed cell lines, transduced cells andcultured cells. The present invention is suitable for use with singlecell types or cell lines; or combinations thereof. In assays thecultured cells may maintain the ability to respond to stimuli thatelicit a response in their naturally occurring counterparts. Culturedcells may have gone through up to five passages or more, sometimes 10passages or more. These may be derived from all sources, particularlymammalian, and with respect to species, e.g., human, simian, rodent,etc., although other sources of cells may be of interest in someinstances, such as plant, fungus, etc.; tissue origin, e.g. heart, lung,liver, brain, vascular, lymph node, spleen, pancreas, thyroid,esophageal, intestine, stomach, thymus, etc.

[0064] In addition, cells that have been genetically altered, e.g. bytransfection or transduction with recombinant genes or by antisensetechnology, to provide a gain or loss of genetic function, may beutilized with the invention. Methods for generating genetically modifiedcells are known in the art, see for example “Current Protocols inMolecular Biology”, Ausubel et al., eds, John Wiley & Sons, New York,N.Y., 2000. The genetic alteration may be a knock-out, usually wherehomologous recombination results in a deletion that knocks outexpression of a targeted gene; or a knock-in, where a genetic sequencenot normally present in the cell is stably introduced.

[0065] A variety of methods may be used in the present invention toachieve a knock-out, including site-specific recombination, expressionof anti-sense or dominant negative mutations, and the like. Knockoutshave a partial or complete loss of function in one or both alleles ofthe endogenous gene in the case of gene targeting. Preferably expressionof the targeted gene product is undetectable or insignificant in thecells being analyzed. This may be achieved by introduction of adisruption of the coding sequence, e.g. insertion of one or more stopcodons, insertion of a DNA fragment, etc., deletion of coding sequence,substitution of stop codons for coding sequence, etc. In some cases theintroduced sequences are ultimately deleted from the genome, leaving anet change to the native sequence.

[0066] Different approaches may be used to achieve the “knock-out”. Achromosomal deletion of all or part of the native gene may be induced,including deletions of the non-coding regions, particularly the promoterregion, 3′ regulatory sequences, enhancers, or deletions of gene thatactivate expression of the targeted genes. A functional knock-out mayalso be achieved by the introduction of an anti-sense construct thatblocks expression of the native genes (for example, see Li and Cohen(1996) Cell 85:319-329). “Knock-outs” also include conditionalknock-outs, for example where alteration of the target gene occurs uponexposure of the animal to a substance that promotes target genealteration, introduction of an enzyme that promotes recombination at thetarget gene site (e.g. Cre in the Cre-lox system), or other method fordirecting the target gene alteration.

[0067] The genetic construct may be introduced into tissues or hostcells by any number of routes, including calcium phosphate transfection,viral infection, microinjection, or fusion of vesicles. Jet injectionmay also be used for intramuscular administration, as described by Furthet al. (1992), Anal Biochem 205:365-368. The DNA may be coated onto goldmicroparticles, and delivered intradermally by a particle bombardmentdevice, or “gene gun” as described in the literature (see, for example,Tang et al. (1992), Nature 356:152-154), where gold microprojectiles arecoated with the DNA, then bombarded into cells.

[0068] A number of selection systems may be used for introducing thegenetic changes, including but not limited to the herpes simplex virusthymidine kinase (Wigler, et al., 1977, Cell 11:223),hypoxanthine-guanine phosphoribosyltransferase (Szybalska & Szybalski,1962, Proc. Natl. Acad. Sci. USA 48:2026), and adeninephosphoribosyltransferase (Lowy, et al., 1980, Cell 22:817) genes can beemployed in tk.sup.-, hgprt.sup.- or aprt.sup.-cells, respectively.Also, antimetabolite resistance can be used as the basis of selectionfor the following genes: dhfr, which confers resistance to methotrexate(Wigler, et al., 1980, Natl. Acad. Sci. USA 77:3567; O'Hare, et al.,1981, Proc. Natl. Acad. Sci. USA 78:1527); gpt, which confers resistanceto mycophenolic acid (Mulligan & Berg, 1981, Proc. Natl. Acad. Sci. USA78:2072); neo, which confers resistance to the aminoglycoside G-418(Colberre-Garapin, et al., 1981, J. Mol. Biol. 150:1); and hygro, whichconfers resistance to hygromycin (Santerre, et al., 1984, Gene 30:147).

[0069] The literature has ample evidence of cells involved with manyphysiological states of interest, factors involved in inducing changesin the phenotype, and markers resulting from the interaction between thefactors and the target cells affected by the factors. Primary cells fortissues of interest are readily available commercially and can beexpanded as required. Biopsies can serve as a source of cells, bothnormal and diseased cells.

[0070] Cell types that can find use in the subject invention, includeendothelial cells, muscle cells, myocardial, smooth and skeletal musclecells, mesenchymal cells, epithelial cells; hematopoietic cells, such aslymphocytes, including T-cells, such as Th1 T cells, Th2 T cells, Th0 Tcells, cytotoxic T cells; B cells, pre-B cells, etc.; monocytes;dendritic cells; neutrophils; and macrophages; natural killer cells;mast cells; etc.; adipocytes, cells involved with particular organs,such as thymus, endocrine glands, pancreas, brain, such as neurons,glia, astrocytes, dendrocytes, etc. and genetically modified cellsthereof. Hematopoietic cells will be associated with inflammatoryprocesses, autoimmune diseases, etc., endothelial cells, smooth musclecells, myocardial cells, etc. may be associated with cardiovasculardiseases; almost any type of cell may be associated with neoplasias,such as sarcomas, carcinomas and lymphomas; liver diseases with hepaticcells; kidney diseases with kidney cells; etc.

[0071] The cells may also be transformed or neoplastic cells ofdifferent types, e.g. carcinomas of different cell origins, lymphomas ofdifferent cell types, etc. The American Type Culture Collection(Manassas, Va.) has collected and makes available over 4,000 cell linesfrom over 150 different species, over 950 cancer cell lines including700 human cancer cell lines. The National Cancer Institute has compiledclinical, biochemical and molecular data from a large panel of humantumor cell lines, these are available from ATCC or the NCI (Phelps etal. (1996) Journal of Cellular Biochemistry Supplement 2.:32-91).Included are different cell lines derived spontaneously, or selected fordesired growth or response characteristics from an individual cell line;and may include multiple cell lines derived from a similar tumor typebut from distinct patients or sites.

[0072] In addition, cells may be environmentally induced variants ofsingle cell lines: e.g., a responsive cell line, such as a transformedendothelial cell line, split into independent cultures and grown underdistinct conditions, for example with or without cytokines, e.g. IL-1,with or without IFN-(, with or without endothelial growth factors, andin the presence or absence of other cytokines or combinations thereof.Each culture condition then induces specific distinctive changes in thecells, such trat their subsequent responses to an environment change isdistinct, yielding a distinctive biomap. Alternatively, the cells may betransduced or otherwise genetically modified cells.

[0073] The term “environment,” or “culture condition” encompasses cells,medir, factors, time and temperature. Environments may also includedrugs and other compounds, particular atmospheric conditions, pH, saltcomposition, minerals, etc. The conditions will be controlled and thebiomap will reflect the similarities and differences between each of theassay combinations involving a different environment or culturecondition.

[0074] Culture of cells is typically performed in a sterile environment,for example, at 37° C. in an incubator containing a humidified 92-95%air/5-8% CO₂ atmosphere. Cell culture may be carried out in nutrientmixtures containing undefined biological fluids such as fetal calfserum, or media which is fully defined and serum free.

[0075] Some preferred environments include environments thatdiscriminate or emphasize cell or tissue states associated withpathology in one or more diseases, for example, Th1 versus Th2polarization of effector T cells; prothrombotic; inflammatory (e.g.NFκB, upregulated TNF-β cytokine production, downregulated IL-10, TGFα,etc.; dysregulated proliferation (neoplasia); angiogenesis; etc.)Environments that facilitate discrimination of specific signalingpathways implicated in disease states are also of interest, e.g. NFκB,classic Th1 or Th2 induction environments, etc.

PHYSIOLOGICALLY RELEVANT ASSAY COMBINATION

[0076] Cell culture conditions that reflect multiple aspects of aphysiological state are termed herein a “representation” or “simulation”of the condition of interest, normally the in vivo condition. There areseveral important, and inter-related variables to be considered whensetting up the in vitro counterpart conditions. These include the typesof cells that are involved, the media employed, the conditions for theculture, the presence of biologically active factors in the cell'sphysiological milieu; and the phenotype of the cells, which may bedetermined both in the absence and presence of pharmacologic agents orfor genetically modified and unmodified cells.

[0077] While a single cell can find use in an assay combination,normally the number of cells will be at least 10², usually at least 10³,and conveniently are grown to confluence.

[0078] In many cases the literature has sufficient information toestablish assay combinations to provide a useful biomap. Where theinformation is not available, by using the procedures described in theliterature for identifying markers for diseases, using subtractionlibraries, microarrays for RNA transcription comparisons, proteomic orimmunologic comparisons, between normal and cells in the physiologicstate of interest, using knock-out and knock-in animal models, usingmodel animals that simulate the physiological state, by introducingcells or tissue from one species into a different species that canaccept the foreign cells or tissue, e.g. immunocompromised host, one canascertain the endogenous factors associated with the physiologic stateand the markers that are produced by the cells associated with thephysiologic state.

[0079] Once a biomap of the components of the assay combination havebeen shown to be relevant to a physiologic state of interest, biomapanalysis can be used to optimize cell culture conditions that moreaccurately represent or simulate such physiologic state in vivo, e.g. indisease states of interest. That is, the values for various parametersfrom cells in vivo can be used as a template for the process ofrepresenting those same cells in culture. Additional markers can bededuced and added as a marker to the map. The greater the number ofindividual markers that vary independently of each other, the morerobust the biomap. By optimizing culture conditions and selection ofparameters, a biomap from a cell panel in vitro can be maderepresentative of an in vivo phenotype. In other words, in vitro cultureconditions can be manipulated in order to generate cells having a biomapthat mimics the parameter readout obtained from similar cells in aspecific in vivo state of interest. There will usually be employed forgeneration of the biomap at least about three parameter or markerreadouts, more frequently 4 or more, generally not more than 20, moreusually not more than about 10, that have similar response patterns inthe in vitro and in vivo conditions. A larger number of sharedparameters indicates a greater relevance of the cultured cells for thedisease state and will usually be indicative of a plurality of pathwaysassociated with the physiologic state in vivo. The parameters selectedwill permit the readout of at least 2, more usually, at least about 3 ormore cell pathways.

[0080] If desired, the parameters of the biomap can be optimized byobtaining biomap parameters within an assay combination or panel ofassay combinations using different sets of readout, and using patternrecognition algorithms and statistical analyses to compare and contrastdifferent biomaps of different parameter sets. Parameters are selectedthat provide a biomap that discriminates between changes in theenvironment of the cell culture known to have different modes of action,i.e. the biomap is similar for agents with a common mode of action, anddifferent for agents with a different mode of action. The optimizationprocess allows the identification and selection of a minimal set ofparameters, each of which provides a robust readout, and that togetherprovide a biomap that enables discrimination of different modes ofaction of stimuli or agents. The iterative process focuses on optimizingthe assay combinations and readout parameters to maximize efficiency andthe number of signaling pathways and/or functionally different cellstates produced in the assay configurations that can be identified anddistinguished, while at the same time minimizing the number ofparameters or assay combinations required for such discrimination.

[0081] There are established protocols for the culture of diverse celltypes that reflect their in vivo counterparts. Protocols may require theuse of special conditions and selective media to enable cell growth orexpression of specialized cellular functions. Such methods are describedin the following: Animal Cell Culture Techniques (Springer Lab Manual),Clynes (Editor), Springer Verlag, 1998; Animal Cell Culture Methods(Methods in Cell Biology, Vol 57, Barnes and Mather, Eds, AcademicPress, 1998; Harrison and Rae, General Techniques of Cell Culture(Handbooks in Practical Animal Cell Biology), Cambridge UniversityPress, 1997; Endothelial Cell Culture (Handbooks in Practical AnimalCell Biology), Bicknell (Editor), Cambridge University Press, 1996;Human Cell Culture, Cancer Cell Lines Part I: Human Cell Culture,Masters and Palsson, eds., Kluwer Academic Publishers, 1998; Human CellCulture Volume II—Cancer Cell Lines Part 2 (Human Cell Culture Volume2), Masters and Palsson, eds., Kluwer Academic Publishers, 1999; Wilson,Methods in Cell Biology: Animal Cell Culture Methods (Vol 57), AcademicPress, 1998; Current Protocols in Immunology, Coligan et al., eds, JohnWiley & Sons, New York, N.Y., 2000; Current Protocols in Cell Biology,Bonifacino et al., eds, John Wiley & Sons, New York, N.Y., 2000.

[0082] The cell surface expression of various surface and intracellularmarkers, including protein, lipid, nucleic acid, e.g. genetic markers,and carbohydrate is known for a large number of different types ofcells, and can be used as a reference for establishing the exactphenotype of cells in vivo; for determining whether that same phenotypeis present in the cultured cells, for determining the effect of anagent, particularly a pharmacologic agent, on the cells, and the like.The manner in which cells respond to an agent, particularly apharmacologic agent, including the timing of responses, is an importantreflection of the physiologic state of the cell.

[0083] For example, one might determine by histologic and antibodystaining the phenotypes of cells in a biopsy sample from a chronicallyinflamed tissue. This information would be used to determine the typesof cells that are present, and their physiologic state, e.g. activated,responding to a cytokine, etc. and their environment, e.g. presence ofcytokines. A corresponding assay combination is then established fromthe information, which provides the relevant cells in the appropriatestate. A biomap is then derived from the assay combination and controlsto provide an in vitro culture as an appropriate surrogate for the invivo state. Usually, an in vivo response will match multiple parametervalues (i.e. up or down regulation of parameters) to similarlyresponding cells in a “representative” assay combination.

[0084] As indicated previously, for many physiologic states, cell types,factors and markers are known. In addition, concentrations having thedesired induction of change in phenotype are also known. Also asdiscussed above, these conditions can be further optimized by makingvariations in concentrations, ratios, choice of markers, etc. to providemore accurate simulations of the naturally occurring physiologicalstate. Assay combinations that represent in vivo states may go throughan iterative process. Based on the information in the literature orindependently derived, one devises an initial set of culture conditions,which includes combinations of known biologically active factors.Depending on the desired biomap, these factors can include cytokines,chemokines, and other factors, e.g. growth factors, such factors includeGM-CSF, G-CSF, M-CSF, TGF, FGF, EGF, TNF-∀, GH, corticotropin,melanotropin, ACTH, etc., extracellular matrix components, surfacemembrane proteins, such as integrins and adhesins, and other componentsthat are expressed by the targeted cells or their surrounding milieu invivo. Components may also include soluble or immobilized recombinant orpurified receptors, or antibodies against receptors or ligand mimetics.

[0085] For cells, either primary cells or cell lines, that have theappropriate phenotype, e.g. neoplastic cells, factors will be used toprovide an environment that simulates the environment of the neoplasticcells in vivo. Depending on the type of cancer, the cancer cells will beperfused with different factors based on the different cells in theenvironment of the tumor, as well as other factors in the blood inducedby factors secreted by the neoplastic cells. Since the physiology of thecells is influenced by these factors, which in turn will influence theregulation of the parameters to be measured, providing these factorsenhances the approximation of the cells in culture to the cells in vivo,providing for a more accurate readout of the effect of an agent on thecells. Many of these factors will be the same factors described above,but additional factors include factors associated with angiogenesis,such as angiogenin, angiopoietin-1, HGF, PDGF, TNF-α, VEGF, IL-1, IL-4,IL-6, IL-8 and fibronectin.

[0086] An initial set of readout parameters is selected, which normallyincludes parameters that are differentially produced, expressed,modulated or indirectly influenced in response to one or more of thecomponents included in the environment. These parameters normallyinclude molecules of functional importance to the cell and which arerelevant to the state of interest. The readout response of cells ismeasured in response to a defined agent, usually the addition of apharmacologic agent, although in some instances a targeted alteration ingenotype or change in environment may be involved. The resulting biomap(normalized set of parameter values) comprising the presence andrelative amount of the markers will simulate the biomap of the relevantcells in vivo. The assay conditions used to generate the biomap may befurther refined to most closely match the biomap of the cells in vivo inthe physiologic state of interest or mimic at least about 3 features ofinterest of such cells in vivo.

[0087] The same pattern of factors and parameters can be used withgenetically modified cells, where the assay combination has thegenetically modified cell as its variable. The genetically modifiedcells are scored for changes in parameters, as compared to thegenetically unmodified cells. The results are used to develop a biomap,where the biomap of the genetically modified cell can be compared to oneor the other or both of other genetically modified cells and assaycombinations involving exogenous agents. The compiled database ofbiomaps can include both biomaps of genetic modifications, and biomapsfor the effects of other compounds. The biomaps provide identificationof the pathways involved, the relationship of the activities ofexogenous agents to genes, and how the cell modifies its biology inrelation to these changes.

PANELS

[0088] For the most part, the biomap dataset will comprise data from apanel of assay combinations. The panel will be related to the purpose ofthe biomap and may include not only the information that has beendeveloped substantially concurrently with the study, but alsoinformation that has been previously developed under comparableconditions. In one embodiment of the invention, a panel is comprised ofat least one assay combination that provides for a representation of anin vivo state of interest, while other assay combinations in the panelare variants thereof. Frequently a panel will be used that is comprisedof at least one assay combination that provides for simulation ofmultiple pathways of interest, while other assay combinations in thepanel are variants thereof. In other embodiments, a panel may becomprised of multiple, different, in vivo representations; or multipledifferent environmental conditions designed to stimulate multiple cellfunctions and pathways. The number of combinations in a panel may varywith the particular use. For example, the minimum number of assaycombinations will be two for a panel for initial screening that wouldcomprise a single assay combination. A panel for determining how acompound affects multiple cellular pathways or functional cell responseswill usually comprise a plurality of assay combinations, usually atleast about 3, more usually at least about 6, frequently at least about10, and may comprise as many as 20 or more unique assay combinations. Apanel for characterizing the mechanism of action of an active compoundwill usually comprise a plurality of assay combinations, usually atleast about 4, more usually at least 6, frequently at least about 10 andmay be as many as 20 or more unique combinations.

[0089] Desirably, a panel will comprise at least one assay combinationthat represents a basal or normal physiological state of the cell ofinterest, which may have been developed prior to the particular biomapor as part of an assay series, or a state in the presence of thefactors. Assay panels used in the screening methods of the invention cancomprise one or more assay combinations that provide a cultured cellcounterpart to an in vivo condition of interest, where the in vivocondition will be the normal state of a cell of interest, a cell in astate associated with disease, a state associated with an immuneresponse, an infected state, an inflammatory state, a neoplastic state,and the like. Assay panels can also comprise one or more assaycombinations designed to allow discrimination of multiple cellularpathways or functional responses of interest, e.g. because of theirparticipation in physiologic states in vivo.

[0090] In one embodiment, the panel of cells and culture conditionsincludes variants of representative culture condition(s), where singlespecific changes are made in order to expand the biomap dataset, e.g. byproviding combinatorial subsets of factor combinations in differentculture wells, provision of known drugs in the culture medium, utilizingcell variants comprising targeted genetic changes, etc.

[0091] In another embodiment, the panel comprises culture conditionswhere multiple specific changes are made simultaneously to therepresentative environment, e.g. two or more changes, usually not morethan about 6, more usually not more than about 4. Such changes areassociated with the additional information that is engendered by theindicated variations. The variations can include the addition of knowninhibitors of specific pathways. Where the presence of the inhibitor andthe candidate drug result in no change in the modulation of the markersas compared to the absence of the candidate drug, then the candidatedrug is in the same pathway inhibited by the inhibitor and the candidatedrug will usually be at or upstream from the site of intervention of theinhibitor in the pathway. Where a different result is obtained with thepresence of the candidate drug, then it is assumed that the candidatedrug acts on a different pathway or may act downstream from theinhibitor in the same pathway.

[0092] Taking as an example the investigation of an inflammatoryresponse, included in a panel can be (i) an assay combination that isrepresentative of endothelial cells responding to the set ofpro-inflammatory cytokines produced by activated monocytes; (ii) acombination that is representative of these same cells in the presenceof an anti-inflammatory drug; (iii) a basal assay combination in theabsence of proinflammatory cytokines; and (iv) variant assaycombinations that lack specific cytokines or subsets of cytokines; etc.

PARAMETERS

[0093] Parameters are quantifiable components of cells, particularlycomponents that can be accurately measured, desirably in a highthroughput system. A parameter can be any cell component or cell productincluding cell surface determinant, receptor, protein or conformationalor posttranslational modification thereof, lipid, carbohydrate, organicor inorganic molecule, nucleic acid, e.g. mRNA, DNA, etc. or a portionderived from such a cell component or combinations thereof. While mostparameters will provide a quantitative readout, in some instances asemi-quantitative or qualitative result will be acceptable. Readouts mayinclude a single determined value, or may include mean, median value orthe variance, etc. Characteristically a range of parameter readoutvalues will be obtained for each parameter from a multiplicity of thesame assay combinations, usually at least about 2 of the same assaycombination will be performed to provide a value. Variability isexpected and a range of values for each of the set of test parameterswill be obtained using standard statistical methods with a commonstatistical method used to provide single values.

[0094] Markers are selected to serve as parameters based on thefollowing criteria, where any parameter need not have all of thecriteria: the parameter is modulated in the physiological condition thatone is simulating with the assay combination; the parameter is modulatedby a factor that is available and known to modulate the parameter invitro analogous to the manner it is modulated in vivo; the parameter hasa robust response that can be easily detected and differentiated and isnot too sensitive to concentration variation, that is, it will notsubstantially differ in its response to an over two-fold change; theparameter is secreted or is a surface membrane protein or other readilymeasurable component; the parameter desirably requires not more than twofactors to be produced; the parameter is not co-regulated with anotherparameter, so as to be redundant in the information provided; and insome instances, changes in the parameter are indicative of toxicityleading to cell death. The set of parameters selected is sufficientlylarge to allow distinction between reference patterns, whilesufficiently selective to fulfill computational requirements.

[0095] For each assay combination, certain parameters will befunctionally relevant and will be altered in response to test orreference agents or conditions, while other parameters may remain staticin that particular combination. Biomaps will generally comprise onlyfunctionally relevant parameter information, although a static parametermay serve as an internal control. A typical biomap will comprise datafrom at least 3 functionally relevant parameters, more usually at leastabout 5 functionally relevant parameters, and may include 10 or morefunctionally relevant parameters, usually not more than about 30, moreusually not more than about 20, parameters. In analyzing the data fromthe biomap, all of the parameters need not be weighed equally. Thoseparameters that are closely functionally associated with the diseasestate or pathophysiologic response, and/or with modulation of cellpathways of interest may be given greater weight in evaluating acandidate drug or a readout, as compared to other parameters that aresuggestive, but do not have as strong an association.

[0096] Parameters of interest include detection of cytoplasmic, cellsurface or secreted biomolecules, frequently biopolymers, e.g.polypeptides, polysaccharides, polynucleotides, lipids, etc. Cellsurface and secreted molecules are a preferred parameter type as thesemediate cell communication and cell effector responses and can be morereadily assayed. In one embodiment, parameters include specificepitopes. Epitopes are frequently identified using specific monoclonalantibodies or receptor probes. In some cases the molecular entitiescomprising the epitope are from two or more substances and comprise adefined structure; examples include combinatorially determined epitopesassociated with heterodimeric integrins. A parameter may be detection ofa specifically modified protein or oligosaccharide, e.g. aphosphorylated protein, such as a STAT transcriptional protein; orsulfated oligosaccharide, or such as the carbohydrate structure SialylLewis x, a selectin ligand. The presence of the active conformation of areceptor may comprise one parameter while an inactive conformation of areceptor may comprise another, e.g. the active and inactive forms ofheterodimeric integrin α_(M)β₂ or Mac-1.

[0097] A parameter may be defined by a specific monoclonal antibody or aligand or receptor binding determinant. Parameters may include thepresence of cell surface molecules such as CD antigens (CD1-CD247), celladhesion molecules including α₄β₇ and other integrins, selectin ligands,such as CLA and Sialyl Lewis x, and extracellular matrix components.Parameters may also include the presence of secreted products such aslymphokines, including IL-2, IL-4, IL-6, growth factors, etc. (LeukocyteTyping VI, T. Kishimoto et al., eds., Garland Publishing, London,England, 1997); Chemokines in Disease: Biology and Clinical Research(Contemporary Immunology), Hebert, Ed., Humana Press, 1999.

[0098] For activated T cells these parameters may include IL-1R, IL-2R,IL4R, IL-12Rβ, CD45RO, CD49E, tissue selective adhesion molecules,homing receptors, chemokine receptors, CD26, CD27, CD30 and otheractivation antigens. Additional parameters that are modulated duringactivation include MHC class II; functional activation of integrins dueto clustering and/or conformational changes; T cell proliferation andcytokine production, including chemokine production. Of particularimportance is the regulation of patterns of cytokine production, thebest-characterized example being the production of IL-4 by Th2 cells,and interferon-(by Th1 T cells. The ability to shift cytokine productionpatterns in vivo is a powerful means of modulating pathologic immuneresponses, for example in models of EAE, diabetes, inflammatory boweldisease, etc. Thus, the expression of secreted cytokines may be apreferred class of parameters, detectable, for example, by ELISAanalysis of the supernatants, etc.

CANDIDATE AGENTS

[0099] Candidate agents of interest are biologically active agents thatencompass numerous chemical classes, primarily organic molecules, whichmay include organometallic molecules, inorganic molecules, geneticsequences, etc. An important aspect of the invention is to evaluatecandidate drugs, select therapeutic antibodies and protein-basedtherapeutics, with preferred biological response functions. Candidateagents comprise functional groups necessary for structural interactionwith proteins, particularly hydrogen bonding, and typically include atleast an amine, carbonyl, hydroxyl or carboxyl group, frequently atleast two of the functional chemical groups. The candidate agents oftencomprise cyclical carbon or heterocyclic structures and/or aromatic orpolyaromatic structures substituted with one or more of the abovefunctional groups. Candidate agents are also found among biomolecules,including peptides, polynucleotides, saccharides, fatty acids, steroids,purines, pyrimidines, derivatives, structural analogs or combinationsthereof.

[0100] Included are pharmacologically active drugs, genetically activemolecules, etc. Compounds of interest include chemotherapeutic agents,anti-inflammatory agents, hormones or hormone antagonists, ion channelmodifiers, and neuroactive agents. Exemplary of pharmaceutical agentssuitable for this invention are those described in, “The PharmacologicalBasis of Therapeutics,” Goodman and Gilman, McGraw-Hill, New York, N.Y.,(1996), Ninth edition, under the sections: Drugs Acting at Synaptic andNeuroeffector Junctional Sites; Drugs Acting on the Central NervousSystem; Autacoids: Drug Therapy of Inflammation; Water, Salts and Ions;Drugs Affecting Renal Function and Electrolyte Metabolism;Cardiovascular Drugs; Drugs Affecting Gastrointestinal Function; DrugsAffecting Uterine Motility; Chemotherapy of Parasitic Infections;Chemotherapy of Microbial Diseases; Chemotherapy of Neoplastic Diseases;Drugs Used for Immunosuppression; Drugs Acting on Blood-Forming organs;Hormones and Hormone Antagonists; Vitamins, Dermatology; and Toxicology,all incorporated herein by reference. Also included are toxins, andbiological and chemical warfare agents, for example see Somani, S. M.(Ed.), “Chemical Warfare Agents,” Academic Press, New York, 1992).

[0101] Test compounds include all of the classes of molecules describedabove, and may further comprise samples of unknown content. Of interestare complex mixtures of naturally occurring compounds derived fromnatural sources such as plants. While many samples will comprisecompounds in solution, solid samples that can be dissolved in a suitablesolvent may also be assayed. Samples of interest include environmentalsamples, e.g. ground water, sea water, mining waste, etc.; biologicalsamples, e.g. lysates prepared from crops, tissue samples, etc.;manufacturing samples, e.g. time course during preparation ofpharmaceuticals; as well as libraries of compounds prepared foranalysis; and the like. Samples of interest include compounds beingassessed for potential therapeutic value, i.e. drug candidates.

[0102] The term samples also includes the fluids described above towhich additional components have been added, for example components thataffect the ionic strength, pH, total protein concentration, etc. Inaddition, the samples may be treated to achieve at least partialfractionation or concentration. Biological samples may be stored if careis taken to reduce degradation of the compound, e.g. under nitrogen,frozen, or a combination thereof. The volume of sample used issufficient to allow for measurable detection, usually from about 0.1:1to 1 ml of a biological sample is sufficient.

[0103] Compounds, including candidate agents, are obtained from a widevariety of sources including libraries of synthetic or naturalcompounds. For example, numerous means are available for random anddirected synthesis of a wide variety of organic compounds, includingbiomolecules, including expression of randomized oligonucleotides andoligopeptides. Alternatively, libraries of natural compounds in the formof bacterial, fungal, plant and animal extracts are available or readilyproduced. Additionally, natural or synthetically produced libraries andcompounds are readily modified through conventional chemical, physicaland biochemical means, and may be used to produce combinatoriallibraries. Known pharmacological agents may be subjected to directed orrandom chemical modifications, such as acylation, alkylation,esterification, amidification, etc. to produce structural analogs.

GENETIC AGENTS

[0104] As used herein, the term “genetic agent” refers topolynucleotides and analogs thereof, which agents are tested in thescreening assays of the invention by addition of the genetic agent to acell. The introduction of the genetic agent results in an alteration ofthe total genetic composition of the cell. Genetic agents such as DNAcan result in an experimentally introduced change in the genome of acell, generally through the integration of the sequence into achromosome. Genetic changes can also be transient, where the exogenoussequence is not integrated but is maintained as an episomal agents.Genetic agents, such as antisense oligonucleotides, can also affect theexpression of proteins without changing the cell's genotype, byinterfering with the transcription or translation of mRNA. The effect ofa genetic agent is to increase or decrease expression of one or moregene products in the cell.

[0105] Introduction of an expression vector encoding a polypeptide canbe used to express the encoded product in cells lacking the sequence, orto over-express the product. Various promoters can be used that areconstitutive or subject to external regulation, where in the lattersituation, one can turn on or off the transcription of a gene. Thesecoding sequences may include full-length cDNA or genomic clones,fragments derived therefrom, or chimeras that combine a naturallyoccurring sequence with functional or structural domains of other codingsequences. Alternatively, the introduced sequence may encode ananti-sense sequence; be an anti-sense oligonucleotide; encode a dominantnegative mutation, or dominant or constitutively active mutations ofnative sequences; altered regulatory sequences, etc.

[0106] In addition to sequences derived from the host cell species,other sequences of interest include, for example, genetic sequences ofpathogens, for example coding regions of viral, bacterial and protozoangenes, particularly where the genes affect the function of human orother host cells. Sequences from other species may also be introduced,where there may or may not be a corresponding homologous sequence.

[0107] A large number of public resources are available as a source ofgenetic sequences, e.g. for human, other mammalian, and human pathogensequences. A substantial portion of the human genome is sequenced, andcan be accessed through public databases such as Genbank. Resourcesinclude the uni-gene set, as well as genomic sequences. For example, seeDunham et al. (1999) Nature 402, 489-495; or Deloukas et al. (1998)Science 282, 744-746.

[0108] cDNA clones corresponding to many human gene sequences areavailable from the IMAGE consortium. The international IMAGE Consortiumlaboratories develop and array cDNA clones for worldwide use. The clonesare commercially available, for example from Genome Systems, Inc., St.Louis, Mo. Methods for cloning sequences by PCR based on DNA sequenceinformation are also known in the art.

[0109] In one embodiment, the genetic agent is an antisense sequencethat acts to reduce expression of the complementary sequence. Antisensenucleic acids are designed to specifically bind to RNA, resulting in theformation of RNA-DNA or RNA-RNA hybrids, with an arrest of DNAreplication, reverse transcription or messenger RNA translation.Antisense molecules inhibit gene expression through various mechanisms,e.g. by reducing the amount of mRNA available for translation, throughactivation of RNAse H, or steric hindrance. Antisense nucleic acidsbased on a selected nucleic acid sequence can interfere with expressionof the corresponding gene. Antisense nucleic acids can be generatedwithin the cell by transcription from antisense constructs that containthe antisense strand as the transcribed strand.

[0110] The anti-sense reagent can also be antisense oligonucleotides(ODN), particularly synthetic ODN having chemical modifications fromnative nucleic acids, or nucleic acid constructs that express suchanti-sense molecules as RNA. One or a combination of antisense moleculesmay be administered, where a combination may comprise multiple differentsequences. Antisense oligonucleotides will generally be at least about7, usually at least about 12, more usually at least about 20 nucleotidesin length, and not more than about 500, usually not more than about 50,more usually not more than about 35 nucleotides in length, where thelength is governed by efficiency of inhibition, specificity, includingabsence of cross-reactivity, and the like.

[0111] A specific region or regions of the endogenous sense strand mRNAsequence is chosen to be complemented by the antisense sequence.Selection of a specific sequence for the oligonucleotide may use anempirical method, where several candidate sequences are assayed forinhibition of expression of the target gene. A combination of sequencesmay also be used, where several regions of the mRNA sequence areselected for antisense complementation.

[0112] Antisense oligonucleotides can be chemically synthesized bymethods known in the art. Preferred oligonucleotides are chemicallymodified from the native phosphodiester structure, in order to increasetheir intracellular stability and binding affinity. A number of suchmodifications have been described in the literature, which alter thechemistry of the backbone, sugars or heterocyclic bases. Among usefulchanges in the backbone chemistry are phosphorothioates;phosphorodithioates, where both of the non-bridging oxygens aresubstituted with sulfur; phosphoroamidites; alkyl phosphotriesters andboranophosphates. Achiral phosphate derivatives include3′-O′-5′-S-phosphorothioate, 3′-S-5′-O-phosphorothioate,3′-CH₂-5′-O-phosphonate and 3′-NH-5′-O-phosphoroamidate. Peptide nucleicacids replace the entire ribose phosphodiester backbone with a peptidelinkage. Sugar modifications are also used to enhance stability andaffinity, e.g. morpholino oligonucleotide analogs. The α-anomer ofdeoxyribose may be used, where the base is inverted with respect to thenatural β-anomer. The 2′-OH of the ribose sugar may be altered to form2′-O-methyl or 2′-O-allyl sugars, which provides resistance todegradation without comprising affinity.

[0113] As an alternative method, dominant negative mutations are readilygenerated for corresponding proteins. These may act by several differentmechanisms, including mutations in a substrate-binding domain; mutationsin a catalytic domain; mutations in a protein binding domain (e.g.multimer forming, effector, or activating protein binding domains);mutations in cellular localization domain, etc. See Rodriguez-Frade etal. (1999) P.N.A.S. 96:3628-3633; suggesting that a specific mutation inthe DRY sequence of chemokine receptors can produce a dominant negativeG protein linked receptor; and Mochly-Rosen (1995) Science 268:247.

[0114] A mutant polypeptide may interact with wild-type polypeptides(made from the other allele) and form a non-functional multimer. Forexample, as has been described for dominant negative mutants of theepidermal growth factor receptor and the chemokine receptor CCR2(Kashles, 1991, Mol. Cell Biol, 11:1454; Rodriguez-Frade, 1999, PNAS96:3628). Mutations or deletions of catalytic subunits of signalingmolecules can also create dominant-negative mutants as, for example,dominant negative mutants of ras and rho family GTPases (Porfiri, 1996,J. Biol. Chem. 271:5871; de Pozo, Eur J. Immunol., 1999, 29:3609),protein tyrosine phosphatase 1B (Arregui, 1998, J. Cell Biol. 143:861),and the guanine nucleotide exchange factor CDC25(Mm) (Vanoni, 1999, J.Biol. Chem. 274:36656). Mutations that alter subcellular localizationcan also create dominant negative mutants, as for example, a proteinkinase B dominant negative mutant described by van Weeren (1998, J.Biol. Chem. 273:13150). Mutations that alter adapter function alsocreate dominant negative mutants, as for example dominant negativemutants of the SH2/SH3 adapters Nck and Grb2 (Gupta, 1998, Oncogene,17:2155) and a deletion mutant of STAT5A (Ilaria, 1999, Blood, 93:4154).

[0115] Preferably, the mutant polypeptide will be overproduced. Pointmutations are made that have such an effect. In addition, fusion ofdifferent polypeptides of various lengths to the terminus of a protein,or deletion of specific domains can yield dominant negative mutants.General strategies are available for making dominant negative mutants(see for example, Herskowitz (1987) Nature 329:219, and the referencescited above). Such techniques are used to create loss of functionmutations, which are useful for determining protein function.

[0116] Methods that are well known to those skilled in the art can beused to construct expression vectors containing coding sequences andappropriate transcriptional and translational control signals forincreased expression of an exogenous gene introduced into a cell. Thesemethods include, for example, in vitro recombinant DNA techniques,synthetic techniques, and in vivo genetic recombination. Alternatively,RNA capable of encoding gene product sequences may be chemicallysynthesized using, for example, synthesizers. See, for example, thetechniques described in “Oligonucleotide Synthesis”, 1984, Gait, M. J.ed., IRL Press, Oxford.

[0117] A variety of host-expression vector systems may be utilized toexpress a genetic coding sequence. Expression constructs may containpromoters derived from the genome of mammalian cells, e.g.,metallothionein promoter, elongation factor promoter, actin promoter,etc., from mammalian viruses, e.g., the adenovirus late promoter; thevaccinia virus 7.5K promoter, SV40 late promoter, cytomegalovirus, etc.

[0118] In mammalian host cells, a number of viral-based expressionsystems may be utilized, e.g. retrovirus, lentivirus, adenovirus,herpesvirus, and the like. In cases where an adenovirus is used as anexpression vector, the coding sequence of interest may be ligated to anadenovirus transcription/translation control complex, e.g., the latepromoter and tripartite leader sequence. This chimeric gene may then beinserted in the adenovirus genome by in vitro or in vivo recombination.Insertion in a non-essential region of the viral genome (e.g., region E1or E3) will result in a recombinant virus that is viable and capable ofexpressing the gene product in infected hosts (see Logan & Shenk, 1984,Proc. Natl. Acad. Sci. USA 81:3655-3659). Specific initiation signalsmay also be required for efficient translation of inserted gene productcoding sequences. These signals include the ATG initiation codon andadjacent sequences. Standard systems for generating adenoviral vectorsfor expression on inserted sequences are available from commercialsources, for example the Adeno-X™ expression system from Clontech(Clontechniques (January 2000) p. 10-12).

[0119] In cases where an entire gene, including its own initiation codonand adjacent sequences, is inserted into the appropriate expressionvector, no additional translational control signals may be needed.However, in cases where only a portion of the gene coding sequence isinserted, exogenous translational control signals, including, perhaps,the ATG initiation codon, must be provided. Furthermore, the initiationcodon must be in phase with the reading frame of the desired codingsequence to ensure translation of the entire insert. These exogenoustranslational control signals and initiation codons can be of a varietyof origins, both natural and synthetic. The efficiency of expression maybe enhanced by the inclusion of appropriate transcription enhancerelements, transcription terminators, etc. (see Bittner et al., 1987,Methods in Enzymol. 153:516-544).

[0120] In a preferred embodiment, methods are used that achieve a highefficiency of transfection, and therefore circumvent the need for usingselectable markers. These may include adenovirus infection (see, forexample Wrighton, 1996, J. Exp. Med. 183: 1013; Soares, J. Immunol.,1998, 161: 4572; Spiecker, 2000, J. Immunol 164: 3316; and Weber, 1999,Blood 93: 3685); and lentivirus infection (for example, InternationalPatent Application WO000600; or WO9851810). Adenovirus-mediated genetransduction of endothelial cells has been reported with 100%efficiency. Retroviral vectors also can have a high efficiency ofinfection with endothelial cells, provides virtually 100% report a40-77% efficiency. Other vectors of interest include lentiviral vectors,for examples, see Barry et al. (2000) Hum Gene Ther 11(2):323-32; andWang et al. (2000) Gene Ther 7(3):196-200.

[0121] For the purpose of analysis of the effect of gene over-expressionintroduction of the test gene into a majority of cells (>50%) in aculture is sufficient. This can be achieved using viral vectors,including retroviral vectors (e.g. derived from MoMLV, MSCV, SFFV, MPSV,SNV etc), lentiviral vectors (e.g. derived from HIV-1, HIV-2, SIV, BIV,FIV etc.), adeno-associated virus (MV) vectors, adenoviral vectors (e.g.derived from Ad5 virus), SV40-based vectors, Herpes Simplex Virus(HSV)-based vectors etc. A preferred vector construct will coordinatelyexpress a test gene and a marker gene such that expression of the markergene can be used as an indicator for the expression of the test gene, aswell as for analysis of gene transfer efficiency. This can be achievedby linking the test and a marker gene with an internal ribosomal entrysite (IRES) sequence and expressing both genes from a singlebi-cistronic mRNA. IRES sequence could be from a virus (e.g. EMCV, FMDVetc) or a cellular gene (e.g. elF4G, BiP, Kv1.4 etc). The examples ofmarker genes include drug resistance genes (neo, dhfr, hprt, gpt, bleo,puro etc) enzymes (β-galactosidase, alkaline phosphatase etc)fluorescent genes (e.g. GFP, RFP, BFP, YFP) or surface markers (e.g.CD24, NGFr, Lyt-2 etc). A preferred marker gene is biologically inactiveand can be detected by standard immunological methods. Alternatively, an“epitope tag” could be added to the test gene for detection of proteinexpression. Examples of such “epitope tags” are c-myc and FLAG(Stratagene). A preferred viral vector will have minimal or nobiological effect on the biomap apart from the genetic agent beingtested. An example of such viral vectors are retroviral vectors derivedfrom the MoMLV or related retroviruses, as listed above. By gating onthe population of genetically modified cells, the unmodified cells inthe culture can be excluded from analysis, or can be compared directlywith the genetically modified cells in the same assay combination. Forexample, see Bowman et al. (1998) J. Biol. Chem. 273:28040-28048.

SCREENING METHODS

[0122] Agents are screened for biological activity by adding the agentto at least one and usually a plurality of assay combinations to form apanel of assay combinations, usually in conjunction with assaycombinations lacking the agent. The change in parameter readout inresponse to the agent is measured, desirably normalized, and theresulting biomap may then be evaluated by comparison to referencebiomaps. The reference biomaps may include basal readouts in thepresence and absence of the factors, biomaps obtained with other agents,which may or may not include known inhibitors of known pathways, etc.Agents of interest for analysis include any biologically active moleculewith the capability of modulating, directly or indirectly, the phenotypeof interest of a cell of interest.

[0123] The initial screening, particularly a high-throughput screening,may utilize a panel comprising a single assay combination, whilesecondary and higher screenings will generally utilize several assaycombinations in a panel.

[0124] The agents are conveniently added in solution, or readily solubleform, to the medium of cells in culture. The agents may be added in aflow-through system, as a stream, intermittent or continuous, oralternatively, adding a bolus of the compound, singly or incrementally,to an otherwise static solution. In a flow-through system, two fluidsare used, where one is a physiologically neutral solution, and the otheris the same solution with the test compound added. The first fluid ispassed over the cells, followed by the second. In a single solutionmethod, a bolus of the test compound is added to the volume of mediumsurrounding the cells. The overall concentrations of the components ofthe culture medium should not change significantly with the addition ofthe bolus, or between the two solutions in a flow through method.

[0125] Preferred agent formulations do not include additionalcomponents, such as preservatives, that may have a significant effect onthe overall formulation. Thus preferred formulations consist essentiallyof a biologically active compound and a physiologically acceptablecarrier, e.g. water, ethanol, DMSO, etc. However, if a compound isliquid without a solvent, the formulation may consist essentially of thecompound itself.

[0126] A plurality of assays may be run in parallel with different agentconcentrations to obtain a differential response to the variousconcentrations. As known in the art, determining the effectiveconcentration of an agent typically uses a range of concentrationsresulting from 1:10, or other log scale, dilutions. The concentrationsmay be further refined with a second series of dilutions, if necessary.Typically, one of these concentrations serves as a negative control,i.e. at zero concentration or below the level of detection of the agentor at or below the concentration of agent that does not give adetectable change in the phenotype.

[0127] For identifying the mechanism of action and determining thecellular target, a test agent is evaluated in secondary or “biositeidentifier” assay combinations. Secondary or “biosite identifier” assaycombinations may be related to the primary assay combination, butcontain specific and targeted alterations. These alterations includeaddition or deletion of specific assay components, genetic alterations,or inclusion of specific compounds or interventions. The mechanism ofaction of the test agent is accomplished when identical readout responsepatterns are obtained from assay combinations containing the test agentand assay combinations generated from known specific alterations of theassay combination. Alternative pathway activators include compounds,agents or interventions that stimulate the target pathway throughspecific components along the target pathway and can bypass upstreamregulatory controls. The test agent is evaluated in these assaycombinations and the pathway target step is identified as including themost upstream pathway component activator that is sensitive to testagent.

[0128] Various methods can be utilized for quantifying the presence ofthe selected markers. For measuring the amount of a molecule that ispresent, a convenient method is to label a molecule with a detectablemoiety, which may be fluorescent, luminescent, radioactive,enzymatically active, etc., particularly a molecule specific for bindingto the parameter with high affinity. Fluorescent moieties are readilyavailable for labeling virtually any biomolecule, structure, or celltype. Immunofluorescent moieties can be directed to bind not only tospecific proteins but also specific conformations, cleavage products, orsite modifications like phosphorylation. Individual peptides andproteins can be engineered to autofluoresce, e.g. by expressing them asgreen fluorescent protein chimeras inside cells (for a review see Joneset al. (1999) Trends Biotechnol. 17(12):477-81). Thus, antibodies can begenetically modified to provide a fluorescent dye as part of theirstructure

[0129] The use of high affinity antibody binding and/or structurallinkage during labeling provides dramatically reduced nonspecificbackgrounds, leading to clean signals that are easily detected. Suchextremely high levels of specificity enable the simultaneous use ofseveral different fluorescent labels, where each preferably emits at aunique color. Fluorescence technologies have matured to the point wherean abundance of useful dyes are now commercially available. These areavailable from many sources, including Sigma Chemical Company (St. LouisMo.) and Molecular Probes (Handbook of Fluorescent Probes and ResearchChemicals, Seventh Edition, Molecular Probes, Eugene Oreg.). Otherfluorescent sensors have been designed to report on biologicalactivities or environmental changes, e.g. pH, calcium concentration,electrical potential, proximity to other probes, etc. Methods ofinterest include calcium flux, nucleotide incorporation, quantitativePAGE (proteomics), etc.

[0130] Highly luminescent semiconductor quantum dots (zincsulfide-capped cadmium selenide) have been covalently coupled tobiomolecules for use in ultrasensitive biological detection (Stupp etal. (1997) Science 277(5330):1242-8; Chan et al. (1998) Science281(5385):2016-8). Compared with conventional fluorophores, quantum dotnanocrystals have a narrow, tunable, symmetric emission spectrum and arephotochemically stable (Bonadeo et al. (1998) Science 282(5393):1473-6).The advantage of quantum dots is the potential for exponentially largenumbers of independent readouts from a single source or sample.

[0131] Multiple fluorescent labels can be used on the same sample andindividually detected quantitatively, permitting measurement of multiplecellular responses simultaneously. Many quantitative techniques havebeen developed to harness the unique properties of fluorescenceincluding: direct fluorescence measurements, fluorescence resonanceenergy transfer (FRET), fluorescence polarization or anisotropy (FP),time resolved fluorescence (TRF), fluorescence lifetime measurements(FLM), fluorescence correlation spectroscopy (FCS), and fluorescencephotobleaching recovery (FPR) (Handbook of Fluorescent Probes andResearch Chemicals, Seventh Edition, Molecular Probes, Eugene Oreg.).

[0132] Depending upon the label chosen, parameters may be measured usingother than fluorescent labels, using such immunoassay techniques asradioimmunoassay (RIA) or enzyme linked immunosorbance assay (ELISA),homogeneous enzyme immunoassays, and related non-enzymatic techniques.These techniques utilize specific antibodies as reporter molecules,which are particularly useful due to their high degree of specificityfor attaching to a single molecular target. U.S. Pat. No. 4,568,649describes ligand detection systems, which employ scintillation counting.These techniques are particularly useful for protein or modified proteinparameters or epitopes, or carbohydrate determinants. Cell readouts forproteins and other cell determinants can be obtained using fluorescentor otherwise tagged reporter molecules. Cell based ELISA or relatednon-enzymatic or fluorescence-based methods enable measurement of cellsurface parameters and secreted parameters. Capture ELISA and relatednon-enzymatic methods usually employ two specific antibodies or reportermolecules and are useful for measuring parameters in solution. Flowcytometry methods are useful for measuring cell surface andintracellular parameters, as well as shape change and granularity andfor analyses of beads used as antibody- or probe-linked reagents.Readouts from such assays may be the mean fluorescence associated withindividual fluorescent antibody-detected cell surface molecules orcytokines, or the average fluorescence intensity, the medianfluorescence intensity, the variance in fluorescence intensity, or somerelationship among these.

[0133] As an example, Luminex beads or other fluorescent beads, or beadsvarying in light scattering parameters can be conjugated to antibodiesto cytokines or other parameters, or conjugated to protein receptors forparameters. The conjugated beads are added to the cells, cell lysate, orto the removed supernatant, allowing bead binding to target parameters.Also, fluorescent antibody to a distinct epitope of the target parameteris used to measure the level of target parameter bound. The fluorescenceand light scatter characteristics of the beads constitute an identifierof the target parameter, and fluorescence derived from added antibody tothe target parameter is an indication of the quantity of targetparameter bound, and hence a readout of the individual parameter.

[0134] Flow cytometry may be used to quantitate parameters such as thepresence of cell surface proteins or conformational or posttranslationalmodification thereof; intracellular or secreted protein, wherepermeabilization allows antibody (or probe) access, and the like.Brefeldin A is commonly utilized to prevent secretion of intracellularsubstances. Flow cytometry methods are known in the art, and describedin the following: Flow Cytometry and Cell Storing (Springer Lab Manual),Radbruch, Ed., Springer Verlag, 2000; Ormerod, Flow Cytometry, SpringerVerlag, 1999; Flow Cytometry Protocols (Methods in Molecular Biology, No91), Jaroszeski and Heller, Eds., Humana Press, 1998; Current Protocolsin Cytometry, Robinson et al., eds, John Wiley & Sons, New York, N.Y.,2000. The readouts of selected parameters are capable of being readsimultaneously, or in sequence during a single analysis, as for examplethrough the use of fluorescent antibodies to cell surface molecules. Asan example, these can be tagged with different fluorochromes,fluorescent bead, tags, e.g. quantum dots, etc., allowing analysis of upto 4 or more fluorescent colors simultaneously by flow cytometry.Plug-flow flow cytometry that has the potential to automate the deliveryof small samples from unpressurized sources at rates compatible withmany screening and assay applications, may allow higher throughput,compatible with high throughput screening, Edwards et al. (1999)Cytometry 37:156-9.

[0135] Both single cell multiparameter and multicell multiparametermultiplex assays, where input cell types are identified and parametersare read by quantitative imaging and fluorescence and confocalmicroscopy are used in the art, see Confocal Microscopy Methods andProtocols (Methods in Molecular Biology Vol. 122.) Paddock, Ed., HumanaPress, 1998. These methods are described in U.S. Pat. No. 5,989,833issued Nov. 23, 1999.

[0136] The quantitation of nucleic acids, especially messenger RNAs, isalso of interest as a parameter. These can be measured by hybridizationtechniques that depend on the sequence of nucleic acid nucleotides.Techniques include polymerase chain reaction methods as well as genearray techniques. See Current Protocols in Molecular Biology, Ausubel etal., eds, John Wiley & Sons, New York, N.Y., 2000; Freeman et al. (1999)Biotechniques 26(1):112-225; Kawamoto et al. (1999) Genome Res9(12):1305-12; and Chen et al. (1998) Genomics 51(3):313-24, forexamples.

[0137] Identifiers of individual cells, for example different cell typesor cell type variants, may be fluorescent, as for example labeling ofdifferent unit cell types with different levels of a fluorescentcompound, and the like. If two cell types are to be mixed, one may belabeled and the other not. If three or more are to be included, each maybe labeled to different levels of fluorescence by incubation withdifferent concentrations of a labeling compound, or for different times.As identifiers of large numbers of cells, a matrix of fluorescencelabeling intensities of two or more different fluorescent colors may beused, such that the number of distinct unit cell types that areidentified is a number of fluorescent levels of one color, e.g.,carboxyfluorescein succinimidyl ester (CFSE), times the number offluorescence levels employed of the second color, e.g.tetramethylrhodamine isothiocyanate (TRITC), or the like, times thenumber of levels of a third color, etc. Alternatively, intrinsic lightscattering properties of the different cell types, or characteristics ofthe biomaps of the test parameters included in the analysis, can be usedin addition to or in place of fluorescent labels as unit cell typeidentifiers.

DATA ANALYSIS

[0138] The comparison of a biomap obtained from a test compound, and areference biomap(s) is accomplished by the use of suitable deductionprotocols, AI systems, statistical comparisons, etc. Preferably, thebiomap is compared with a database of reference biomaps. Similarity toreference biomaps induced by assay combinations involving known pathwaystimuli or inhibitors can provide an initial indication of the cellularpathways targeted or altered by the test stimulus or agent.

[0139] A database of reference biomaps can be compiled. These databasesmay include reference biomaps from panels that include known agents orcombinations of agents that target specific pathways, as well asreferences from the analysis of cells treated under environmentalconditions in which single or multiple environmental conditions orparameters are removed or specifically altered. Reference biomaps mayalso be generated from panels containing cells with genetic constructsthat selectively target or modulate specific cellular pathways. In thisway, a database is developed that can reveal the contributions ofindividual pathways to a complex response.

[0140] The effectiveness of pattern search algorithms in classifyingbiomaps can involve the optimization of the number of parameters andassay combinations. The disclosed techniques for selection of parametersprovide for computational requirements resulting in physiologicallyrelevant outputs. Moreover, these techniques for pre-filtering data sets(or potential data sets) using cell activity and disease-relevantbiological information improve the likelihood that the outputs returnedfrom database searches will be relevant to predicting agent mechanismsand in vivo agent effects.

[0141] For the development of an expert system for selection andclassification of biologically active drug compounds or otherinterventions, the following procedures are employed. For everyreference and test pattern, typically a data matrix is generated, whereeach point of the data matrix corresponds to a readout from a parameter,where data for each parameter may come from replicate determinations,e.g. multiple individual cells of the same type. As previouslydescribed, a data point may be quantitative, semi-quantitative, orqualitative, depending on the nature of the parameter.

[0142] The readout may be a mean, average, median or the variance orother statistically or mathematically derived value associated with themeasurement. The parameter readout information may be further refined bydirect comparison with the corresponding reference readout. The absolutevalues obtained for each parameter under identical conditions willdisplay a variability that is inherent in live biological systems andalso reflects individual cellular variability as well as the variabilityinherent between individuals.

[0143] Classification rules are constructed from sets of training data(i.e. data matrices) obtained from multiple repeated experiments.Classification rules are selected as correctly identifying repeatedreference patterns and successfully distinguishing distinct referencepatterns. Classification rule-learning algorithms may include decisiontree methods, statistical methods, naive Bayesian algorithms, and thelike.

[0144] A knowledge database will be of sufficient complexity to permitnovel test biomaps to be effectively identified and classified. Severalapproaches for generating a sufficiently encompassing set ofclassification patterns, and sufficiently powerfulmathematical/statistical methods for discriminating between them canaccomplish this.

[0145] A database can be compiled by preparing biomaps using differentcombinations of a plurality of biologically active factors, inconjunction with biomaps involving the use of known agents having knowneffects and/or the use of genetically modified cells, where the geneticmodification affects one or more of the pathways affected by one or moreof the factors used to create the phenotype. For example, if the cultureconditions selected to produce a specific in vitro reference patterncontain four biologically active agents, in addition to those present inthe basal conditions of the normal or basal environment, a biomap wouldbe generated from a panel of cells treated under all possiblecombinations of the 4 agents (15 assay conditions), typically usingconstant concentrations in each of the combinations. The extent of thedatabase associated with assay combinations to screen candidates forspecific phenotypes, e.g. indications, will vary with the nature of thephenotype, the amount of information desired, the complexity of thesystem, and the like.

[0146] The data from cells treated with specific drugs known to interactwith particular targets or pathways provide a more detailed set ofclassification readouts. Data generated from cells that are geneticallymodified using over-expression techniques and anti-sense techniques,permit testing the influence of individual genes on the phenotype.

[0147] As indicated, agents may be analyzed in the absence of anyfactors or with a limited number of factors. The assay is performed aspreviously described and the values of the parameters can be compared tothe biomap reflecting the values for the parameters of the physiologicstate of interest, the values of the parameters for the response to oneor more factors, and the basal response. In this way, the effect of theagent under physiological conditions can be evaluated. Similarly, onemay have datasets compiled from combinations of agents to determinetheir effect when combined on cell physiology. Again, with a comparisonof the values obtained for the parameters with the values obtained fromthe parameters with assay combinations employing factors, one canevaluate the effect of the agent combination on various cells in vivo.

[0148] A preferred knowledge database contains reference biomapscomprising data from optimized panels of cells, environments andparameters. For complex environments, data reflecting small variationsin the environment may also be included in the knowledge database, e.g.environments where one or more factors or cell types of interest areexcluded or included or quantitatively altered in, for example,concentration or time of exposure, etc.

PATHWAY DISCRIMINATION

[0149] Biomaps are useful for pathway discrimination where the biomapsassociated with agents that have a common target and mode of action arereproducibly and robustly similar, where biomaps are associated withagents that stimulate or inhibit different pathways of interestreproducibly, and with biomaps that discriminate at least two,preferably three, and more preferably four or more different pathways ina common set of assay combinations.

[0150] Providing an agent to an assay panel results in a biomap thatreflects the cellular response to that agent, produced by the stimulusacting on a target, or biosite, and through a signaling pathway,producing a change in the phenotype of the cell. A pathway may bedefined for the purposes of the invention as a set of interactingcellular events that produces or contributes to a specific phenotype.Pathways are mediated by sets of interacting molecules of the cell.Variables that act on the same cellular pathway result in similarbiomaps. Similarly, variables that act on different cellular pathwaysresult in different biomaps. Variables that act on multiple pathways canstimulate pathway interactions and thus also yield distinctive biomaps.It is not necessary for the purposes of the invention that the cellularpathway is known.

[0151] Comparison of a biomap produced by the action of an agent in apanel, to biomaps in the database, will indicate whether the variableyields a cellular state similar to those generated by other conditions,and thus may indicate a mechanism of action in the cell, and/or mayindicate specific relevance of the biological activity to a particulardisease or other state.

[0152] Importantly, compounds that alter therapeutically relevantparameters are of potential interest as drugs. For example, compoundsthat inhibit cytokine up-regulation of inflammatory cytokines or ofmolecules (adhesion molecules, chemokines, etc.) involved in leukocytetrafficking to inflamed tissues may have therapeutic value ininflammatory diseases. Compounds that inhibit oncogenic proteins,transcription factors involved with pathways essential to neoplasticproliferation, cyclins, kinases, etc., indicate initial interest asdrugs for the treatment of cancer. Compounds that enhance pathwaysassociated with cholesterol metabolism and transport may havetherapeutic value in cardiovascular diseases.

OPTIMIZATION TECHNIQUES

[0153] Optimized assay combinations can be developed by repeating theprocedure of testing parameter readouts in response to stimuli until theselected disease-relevant environment is sufficiently differentiatedfrom the normal or another selected condition and an optimized parameterset is selected.

[0154] Optimization of an initial assay combination includes theidentification of optimal concentrations of added biologically activeagents, the timing of their addition, addition or deletion of factors,and selection of an optimal time course. The time course will dependupon whether one is interested in the effect of an agent prior to theaddition or at the time of the addition of the factors influencing theparameters or after the physiological condition has been established, aswell as having cells that do and do not present the physiologiccondition. The factors may have been present from about 0 to 72 h orlonger prior to the addition of the agent, usually from about 0 to 48 h,and frequently from about 0 to 24 h. Where the cells may be at variousstages of the physiologic condition, e.g. unchanged, intermediate stageand final stage the factors will usually have been present from about 2to 48 h or longer, more usually from about 6 to 24 h. Optimization alsoincludes modification of the basal medium (e.g. the addition or removalof particular growth factors, extracellular matrix components etc.) toreflect differences between physiologic states of interest.

[0155] For the most part, the concentration of the factors for providingthe physiologic condition will be known and frequently the response willnot be sensitive to small changes in the concentration. Where theconcentration has not been reported, one can determine a usefulconcentration by determining the concentration that provides saturation.This can be achieved using cells and titrating the number of receptorswith a labeled factor, e.g. fluorescent labeled factor. Once thesaturation level is known, one may cut back to about 25 to 75% of thesaturation value and determine the response by analyzing for theparameters of interest and the effect of the reduced concentration ascompared to the response at saturation. Alternatively, take the factorto a plateau of a dependent functional response, add more or less todefine levels maximal to response measures.

[0156] Active compounds alter the cellular responses and readoutpatterns when included in a selected assay combination. Such alterationmay include returning the levels of one or more parameters to theirlevels in the basal condition, or otherwise altering the cellularresponses, particularly when such alterations reflect changes towards adesirable cellular state (e.g. converting Th1-like to Th2-like response,or vice versa).

[0157] Optimal assay combinations yield information about multipledifferent pathways of interest in regulation of inflammatory processes.Conditions based on initial combinations are developed to better reflectthe physiologic or disease-relevant environment. Optimized assaycombinations are developed by repeating the procedure to produce abiomap, evaluating additional combinations of biologically active agentsand/or different parameters, until the biomap produced under theselected disease-relevant environment is sufficiently differentiatedfrom the biomap of the normal or another selected condition and anoptimized parameter set is selected.

CELL FAMILIES ENDOTHELIAL CELLS

[0158] As exemplary of the subject situation, primary endothelial cellsare employed in one embodiment of the invention, as these cells respondto a large variety of cellular stimuli. Endothelial cells are highlysensitive to their environment, and they contain a large number ofsignaling pathways. This provides an opportunity to evaluate the effectof compounds on many pathways and/or pathway interactions. Endothelialcells participate in many disease processes. In inflammation, theycontrol the migration and localization of effector leukocytes andlymphocytes; in cancer, they control the nutrition of tumors anddissemination of metastases; and their dysregulation is centrallyimportant to cardiovascular disease.

[0159] The present invention is useful for identifying regulators ofinflammation using human endothelial cells as an indicator cell type.Endothelial cells are found in inflammatory tissues; they are highlyresponsive to environmental stimuli; and they are a cell type for whichprimary cells can be readily isolated and cultured such that they retainresponsiveness to many of the biologically active factors important toinflammatory and other processes. Vascular endothelial cells are apreferred cell type because they participate in the inflammatory diseaseprocess by regulating the type of leukocytes that are recruited to thetarget tissue. The specificity of recruitment is determined by thecombinatorial expression of adhesion molecules and chemokines. A set ofculture systems or assay combinations that mimic the response of theendothelial cells to different types of inflammatory processes have beendeveloped in vitro using the methods of the invention.

[0160] A number of factors are known to be associated with endothelialcells, such as EGF, FGF, VEGF, insulin, etc., cytokines, such as theinterleukins, including IL-1 IL-3, IL-4, IL-8 and IL-13; interferons,including IFN-α, IFN-β, IFN-γ; chemokines; TNF-α, TGFβ, proangiogenicand anti-angiogenic factors, etc. (See Current Protocols in Immunology,supra).

[0161] Endothelial cells in inflammatory tissues from chronicinflammatory disease patients differ from endothelial cells in normaltissues by increased expression parameters including ICAM-1, E-selectin,IL-8 and HLA-DR [Nakamura S, Lab Invest 1993, 69:77-85; Geboes K,Gastroenterology 1992, 103:439-47; Mazzucchelli L, J Pathol 1996,178:201-6]. In addition, each of these parameters has been demonstratedto function in the inflammatory disease process. ICAM-1 and E-selectinare cell adhesion molecules that contribute to the localization andactivity of inflammatory cells including T cells, monocytes, andneutrophils. IL-8 is a neutrophil chemoattractant and HLA-DRparticipates in the activity of pathologic T cells. Other cell surfaceor secreted parameters include parameters that are known to be regulatedby factors, such as VCAM-1, which is induced on endothelial cells byTNF-α or IFN-γ; IL-10 and MIG which are induced on endothelial cells byIFN-γ; or GRO-α or ENA-78 which are induced on endothelial cells by IL-1and/or TNF-α [Goebeler M, J Invest Dermatol 1997, 108:445-51; Piali LEur J Immunol. 1998, 28:961-72].

[0162] For assay combinations representative of chronic inflammatorydiseases, the cytokine IL-1 is often found in combination with TNF-α andIFN-γ in such diseases, for example, in Crohn's disease (Autschbach,1995, Virchows Arch. 426:51-60). For this inflammation model ofendothelial cells, an inhibitor of TNF-∀, such as a neutralizingantibody against TNF-∀, provides an example of an active compound.Adding anti-TNF-α to the assay combination was shown in reducedexpression levels of ICAM-1; VCAM-1; and E-selectin; and increasedexpression levels of CD31.

[0163] Assay combinations that include genetically modified cells arealso a preferred source of reference patterns. For example, TNF-αsignaling in HUVEC involves the NFεB signaling pathway (Collins, 1995,Faseb J, 9:899). Blockade of this pathway can be accomplished byoverexpression of IκB-α, for example, through adenoviral gene transfer(Weber, 1999, Blood 93:3685). HUVEC overexpressing IκB-α express reducedlevels of ICAM-1 or E-selectin in response to TNF-α. However, becauseother cytokines, such as IL-1, can also signal through NFκB, readoutpatterns due to TNF-α inhibition can be distinguished from readoutpatterns that reflect NFκB inhibition.

LEUKOCYTES

[0164] By a similar iterative process as that described above,appropriate assay combinations for endothelial cells representing otherinflammatory, disease, or physiologic states are established. Theseconditions include: psoriasis, rheumatoid arthritis, or chronic Th2disease environments such as asthma, allergy or ulcerative colitis. Achronic Th2 assay combination can be defined by the culture of HUVECwith TNF-α and/or IL-1 and IL4 for 24 hours. Inflammation in chronic Th2environments, such as asthma, is characterized by the presence of TNF-α,IL-1 and IL4, but not IFN-γ [Robinson, 1993, J. Allergy Clin. Immunol.92:313]. HUVEC cultured for 24 hours with TNF-α and IL4 express highlevels of VCAM and MCP-1, similar to the in vivo situation [Ohkawarea,1995, Am J. Resp. Cell Mol. Biol. 12:4; Rozyk, 1997, Immunol. Lett.58:47].

[0165] Lymphokine-producing activated lymphocytes (CD45RO+, CD44hi,etc.) are a hallmark of inflammatory diseases including psoriasis,rheumatoid arthritis, Crohn's disease, ulcerative colitis, asthma, etc.Depending on the disease environment and tissue site, activatedlymphocytes can differ in their expression and function of adhesionmolecules and other receptors, as well as in their production of variouscytokines and other factors. The ability to selectively block lymphocyteactivation associated with the inflammatory disease without inhibitingor suppressing lymphocyte activation associated with the ability tofight infection and neoplasia is a goal of inflammatory drug therapy.

[0166] Specific homing and adhesion receptors, as well as chemokinereceptors, expressed by lymphocytes differentiating into effector andmemory cells target the involved regulatory and cytotoxic T cellpopulations, as well as B cells responsible for humoral immunity.Upregulation and modulation of homing receptor expression patterns isobserved when lymphocytes are activated in defined microenvironmentscomprising specific cytokines; and in some environments multiple homingreceptors (e.g., α₄β₇, the cutaneous lymphocyte antigen (“CLA”),inflammatory chemokine receptor such as CCR5 and CXCR3 and bonzo, etc.)are induced. Multiplex analysis of each of these homing receptorparameters, which may also be performed in conjunction with other knownor discovered parameters in reflecting the cellular state of activation,can be used to select immunomodulatory compounds capable of shiftingpatterns of homing receptor expression in a common microenvironment.Such modulators of lymphocyte targeting can be powerfulimmunosuppressives for localized immune pathologies, as in inflammatorybowel diseases, psoriasis, multiple sclerosis, arthritis, and the like;modulating patterns of lymphocyte homing/targeting molecules they wouldmodulate in vivo immune responses therapeutically without the sideeffects associated with generalized immunosuppression.

[0167] The present invention can be applied to screening for drugs thatblock selective leukocyte activation pathways. Cells can be normallymphocytes or lymphocyte subsets isolated from human blood or tissuesaccording to standard methods (Current protocols in Immunology), or celllines selected for their ability to respond in a similar fashion as donormal cells, or other cells.

[0168] The assay conditions for these cells include (1) known activationconditions ((combinations ofanti-CD3+IL-2+/−IL4+/−IFN-(+/−IL-12+/−anti-IL-4 or anti-IFN-γ). Suchconditions are given in: T Cell Protocols: Development and Activation(Methods in Molecular Biology, 134), Kearse, Ed., Humana Press, 2000.);(2) culture conditions that represent in vivo disease environments; or(3) conditions that emphasize or discriminate known signaling pathwaysor specific signaling pathways implicated in disease states. Assaycombinations and reference biomaps are identified for a variety ofdiseases, including psoriasis, arthritis, Crohn's disease, ulcerativecolitis, asthma, etc. by the iterative process as described in Example1, of defining environmental conditions and initial parameter sets fromin vivo data, testing assay combinations in vitro, comparing the invitro and in vivo biomaps, optimizing the assay combination andselection of an optimal parameter set.

[0169] The disease environment in psoriasis includes IL-12, IFN-γ andTNF-α (Yawalker, 1998, J. Invest. Dermatol. 111:1053; Austin, 1999, J.Invest. Dermatol. 113:752), therefore an assay combination for psoriasiswill include one or more, usually at least two, and frequently all ofthese factors. Inflammatory T cells in psoriasis express high levels ofthe CLA antigen, a carbohydrate antigen related to Sialyl Lewis x (Berg,1991, J. Exp. Med. 174:1461; Picker, 1990, Am. J. Pathol. 136:1053).Therefore a parameter set for psoriasis will contain the CLA antigen.

[0170] The disease environment in Crohn's disease includes IL-1, TNF-α,IL-6, IL-8, IL-12, IL-18, and IFN-γ (Daig, 1996; Woywodt, 1994; Kakazu,1999; Pizarro, 1999; Monteleone, 1999), therefore an assay combinationfor Crohn's disease will include one or more of these factors, generallyincluding at least two of the IL factors, by themselves or incombination with at least one of IFN-γ and TNF-α. T cells ininflammatory bowel disease express high levels of the E7 integrin(Elewaut, 1998, Scand J. Gastroenterol, 33:743), therefore the parameterset for inflammatory bowel diseases preferentially contains E7.

[0171] The disease environment in rheumatoid arthritis includes TNF-α,IL-1, IL-6, IL-10, IL-15, MIP1, MCP-1, and TGF (Robinson, 1995, Clin.Exp. Immunol. 101:398; Thurkow, 1997, J. Pathol. 181:444; Suzuki, 1999,Int. Immunol, 11:553), therefore an assay combination for arthritis willinclude one or more of these factors, generally including at least twoof the IL factors and at least one of MIP1 and MCP-1. T cells inrheumatoid arthritis synovial fluid express CCR5 and CXCR3 (Suzuki,1999; Qin, 1998, J. Clin. Invest. 101:746; Loetscher, 1998, Nature391:344), therefore the parameter set for rheumatoid arthritispreferentially contains CCR5 and CXCR3.

[0172] The disease environment in asthma includes IL-1α, IL-4, IL-5,IL-6 and GM-CSF (Miadonna, 1997; Walker, 1994), therefore, an assaycombination for asthma will contain one or more of these factors,generally including at least two of the IL factors and GM-CSF.

[0173] Once the optimal environmental conditions representing the targetdisease are determined, cells are treated with candidate drugs in thoseenvironments and the selected parameters are measured. Comparing thebiomaps obtained in the presence of drugs with reference biomaps enablesthe identification of drugs that inhibit lymphocyte responses to complexenvironments, and enables them to be differentiated from drugs that acton selective pathway components. The multiplex living response systemsallows simultaneous analysis of multiple activation-associatedparameters, and Th1 versus Th2 phenotypes; as well as comparison of theeffects candidate drugs have on T cell activation programs with theireffects on properties of other cells in the living response systemutilized. As an example, in its simplest embodiment, normal human Tcells or blood lymphocytes are incubated in an activating and/ordifferentiating environment, contacted with an agent, and the readoutoutput patterns compared with reference patterns obtained under controlconditions (without the compound) and in the presence of prototypicalanti-inflammatory compounds etc.

[0174] This is accomplished by developing a database of referencebiomaps developed from the analysis of cells treated under environmentalconditions in which single components are removed, or with known drugsthat target specific pathways. Alternatively, reference biomaps aregenerated in the presence of genetic constructs that selectively target,stimulate, inhibit or otherwise modulate specific pathways. In this way,a database of reference biomaps is developed.

[0175] One preferential application of the invention is in immunedeviation. Certain inflammatory diseases result or are exacerbated bypolarization of an inflammatory response towards Th1 or Th2. Forexample, conditions that promote Th1 responses (e.g. systemic treatmentwith IFN-γ) exacerbate certain diseases such as multiple sclerosis. Bythe procedure given above, compounds can be screened for their abilityto shift biomaps from “Th1” to “Th2”, vice versa, or from “Th1” or “Th2”to other phenotypes.

[0176] The invention is also useful for screening compounds for druginteractions. For example, methotrexate is a current therapy forrheumatoid arthritis and inhibits T cell proliferation. Screeningcompounds in the presence of methotrexate can reveal unexpectedtoxicities or beneficial synergies.

[0177] The present invention can be applied for the identification ofcompounds that induce lymphocyte activation. For this application, drugcompounds may be screened for their ability to induce particularreference biomaps. Such compounds would have clinical utility as immunestimulants, for vaccine protocols and other applications.

[0178] The present invention can be applied to the identification ofcompounds that stimulate or inhibit lymphocyte apoptosis. A variety ofculture conditions are known to induce apoptosis in particular celltypes. For example, radiation; inclusion of FasL in the culture; orother apoptosis inducing agent, can induce apoptosis of FasR (CD95)expressing T cells; TNF-∀ can induce apoptosis under specificconditions; a conformational change in ICAM-3, resulting in a change inligand preference (from LFA-1 to a macrophage receptor) is associatedwith apoptosis in activated T cells, etc. The ability of a drug orintervention to induce apoptosis has applications for therapy oflymphoma and leukemia as well as autoimmune disease. Defining biomapsassociated with apoptosis are useful for identifying active compounds.

MACROPHAGE

[0179] The present invention can be applied to the identification ofcompounds that inhibit or alter macrophage activation. Peripheral bloodmonocytes, tissue macrophages and related cell lines are a preferredcell type for screening for pharmacologically activecompounds/interventions due to their ability to discriminatepathophysiological environments. Monocytes/macrophages in differentphysiological settings have altered responses. IL-4 reduces productionof IL-10 in LPS stimulated blood monocytes but not in synovialmonocyte/macrophages (Bonder (1999) Immunol. 96:529; Ju (1999) Int. Rev.Immunol. 18:485). In addition to being highly responsive to theirenvironment, monocytes/macrophages participate in a variety of diseaseprocesses, including inflammation, fibrosis, and wound healing, throughtheir production of mediators, growth factors, phagocytosis and antigenpresentation functions. Assay combinations, e.g. IL-4 and other ILfactors, M-CSF, and GM-CSF are used in combination with each other orother factors associated with the physiologic or disease environments ofinterest and readout parameter sets are selected that allow differentstates to be distinguished. Readout parameters include integrins,adhesion molecules, and the like. Compounds are added to selected assaycombinations, parameters are measured and the resulting test patternsare compared to reference biomaps. Reference patterns, held in aknowledge database include those developed from the analysis of cellstreated under environmental conditions in which single components areremoved, or with known drugs that target specific pathways.Alternatively, reference biomaps can be generated in the presence ofgenetic constructs that selectively target, stimulate, inhibit orotherwise modulate specific pathways. In this way, a database ofreference biomaps is developed, and compounds are selected by theirability to produce a desired biomap.

MAST CELL

[0180] The present invention can be applied to the identification ofcompounds that inhibit or alter mast cell activation. Such compoundshave utility in the treatment of allergy and asthma, where mast cellproducts mediate disease pathology (Galli, 2000, Curr. Opin. Hematol.7:32). Mast cells display altered responses depending on theirenvironment. The ability of mast cells to produce IL-3 and GM-CSF issignificantly increased in the presence of fibronectin or vitronectin(Kruger-Krasagakes, 1999, Immunology, 98:253). Mast cells inallergen-induced late-phase cutaneous reactions in atopic patientsexpress high levels of the high affinity IgE receptor compared with mastcells in control skin (Ying, 1998, Immunology 93:281). Assaycombinations including at least one of fibronectin and vitronectin aredeveloped that reflect physiologic or disease environments and readoutparameter sets, including at least one of IL-3, GM-CSF, andIgE-receptor, are selected that allow different states to bedistinguished. Compounds are added to selected assay combinations,parameters are measured and the resulting test patterns are compared toreference biomaps. Reference patterns, held in a knowledge databaseinclude those developed from the analysis of cells treated underenvironmental conditions in which single components are removed, or withknown drugs that target specific pathways. Alternatively, referencebiomaps can be generated in the presence of genetic constructs thatselectively target, stimulate, inhibit or otherwise modulate specificpathways. In this way, a database of reference biomaps is developed, andcompounds are selected by their ability to produce a desired biomap.

CANCER APPLICATIONS

[0181] a. Cytolytic/Cytostatic Compounds

[0182] The unique comparisons between panels of cell types holds thepotential to provide therapeutically important information, and allowsubclassification, of drugs and genes that can inhibit neoplastic cellproliferation, alter the immunogenicity, or modulate other criticalfeatures for cancer therapy. A panel of 60 neoplastic cell lines at theNCI has been used to examine the effects of hundreds of anti-cancer andother compounds on neoplastic cell proliferation (Weinstein, 1997,Science 275:343). While the responses of any individual cell linecarried little information about the mechanism of inhibition ofproliferation, the patterns of responses among the 60 cells of the paneldemonstrated a robust ability to distinguish between compounds targetingdifferent mechanisms, and thus to characterize the mechanisms of actionof novel drugs as well, by comparison with reference tumor panelresponse patterns.

[0183] The present invention is applied by identifying subsets of the 60NIH cell lines, and other cell lines that can provide robustdiscriminatory power for identifying and subclassifying anti-canceragents. The responses of cell surface proteins and/or secreted productssuch as chemokines and other cytokines and the like, is determined underenvironmental conditions supportive of the neoplastic proliferativephenotype. Breast cancer environments involve certain growth factors,e.g. angiogenic factors and cytokines, such as IL-10 (Merendino 1999,68, 355). Alterations in the selected parameters by contact of the cellswith anti-cancer agents is used to define reference biomapscharacteristic and diagnostic of individual drugs or mechanisms ofaction. The use of cell surface parameters to identify cytotoxic andcytostatic states allows a panel of cells to be evaluated in parallel.Biomaps are generated from known anti-cancer agents including DNAsynthesis inhibitors, nucleoside analogs, topoisomerase inhibitors,microtubule function inhibitors etc. Such compounds are given inWeinstein, 1997, and The Pharmacologic Basis of Therapeutics. Referencepatterns that distinguish compounds that are cytostatic or cytolyticversus apoptosis-inducing are developed using a panel of primary tumorsand tumor cell lines with and without functioning p53 pathways. Theprocedure of simultaneous multiplex analyses of normal and cancer celllines allows discrimination of agents selective for cancer cells.

[0184] The invention is also useful for screening compounds for druginteractions and synergies. Drug interactions are highly important incancer therapy. For example, while steroids control the edema thatoccurs with glioma, they also interfere with chemotherapy efficacy.Cytotoxic drugs are a main treatment for cancer and interference withthe chemotherapy efficacy may offset the anti-tumor effect of anapoptosis inducer. On the other hand, synergy between individual drugswould be highly beneficial, perhaps allowing reduced doses of theindividual drugs and reducing the side effects.

[0185] b. Inhibitors of Metastatic Phenotype

[0186] The present invention can be applied to the identification ofcompounds or interventions that alter metastatic phenotypes of cancercells. Metastatic cancers have altered adhesive and invasive functions.Metastatic cancers are associated with certain features includingexpression of various oncogenes, such as H-ras, increased levels ofproteolytic enzymes, such as TPA (tissue plasminogen activator),production of osteopontin, and altered adhesion molecule expression andfunction. For example, carcinomas preferentially express α₆β₁ and lessα₂β₁, β₃β₁ and α₅β₁ (Chambers 1993, Crit. Rev. Oncol. 4:95; Dedhar,1995, Cancer Metastasis Rev. 14:165; Tuck, 1999, Oncogene 18:4237).Simultaneous multiplex analyses of normal and cancer cell lines allowsdiscrimination of agents that selectively modulate the metastaticphenotype.

[0187] c. Inducers of Differentiative Phenotypes.

[0188] There is a general inverse relationship between the degree ofcellular differentiation and the rate of cell proliferation in tumors.Several anti-cancer agents stimulate the differentiation and inhibitproliferation of malignant cells, including retinoids, various cytokinesand analogs of vitamin D (Bollag, 1994, J. Cell Biochem. 56:427).All-trans retinoic acid, an agent that induces differentiation, gives ahigh rate of complete clinical remission in the treatment of acutepromyelocytic leukemia (Tallman, 1994, Semin Hematol 31 (Suppl 5):38).Agents that stimulate differentiation are not easily detected usingtraditional in vitro assays of anticancer drug activity.

[0189] d. Apoptosis of Tumor Endothelial Cells.

[0190] The present invention can be applied to the identification ofcompounds that induce apoptosis of tumor endothelial cells. For thisapplication, environmental conditions that induce a tumor endothelialcell phenotype on cultured endothelial cells are selected. Typicallythese environments are proangiogenic and contain a variety of growthfactors, such as TGFβ, VEGF and basic FGF, as well as other tumor orother cell derived factors, where these factors can be used in the assaycombination. Tumor endothelium differs from other endothelium byincreased expression of α_(v)β₃. A set of conditions that induceapoptosis of these cells is evaluated and a set of parameters thatdefines a biomap diagnostic of apoptosis is identified. Apoptoticconditions are identified as those that induce DNA laddering, and otherwell described features. These include simple culture conditions thatcontain one or more factors known to induce or promote endothelial cellapoptosis in vitro, such as ceremide, the combination of TNF-∀ and heatshock or sodium arsenite, TNF-α+IFN-γ, oxysterols; TNF-α in the presenceof cyclohexamine, etc. (See Ruegg (1998) Nat. Med. 4:408). Parametersthat may be included in the selected set include a variety of moleculesinvolved in adhesion and proteolysis (since a prominent feature ofapoptotic endothelial cells is their release from the vessel wall),those that can be modulated by individual factors, such as E-selectin,ICAM-1, VCAM and HLA-DR, and molecules or determinants known to bemodulated with apoptosis such as CD95, ICAM-1, CD44, and carbohydratedeterminants (Herbst, 1999, J. Cell Physiol. 181:295; Rapaport, 1999,Glycobiology 9:1337; Hirano (1999) Blood 93:2999; Thomas (1998) J.Immunol. 161:2195; Ma (1998) Eur. J. Hematol. 61:27; Pober (1998)Pathol. Biol. (Paris) 46:159).

[0191] Once a reference biomap for endothelial cell apoptosis isidentified, compounds are screened for their ability to induce a similarbiomap from tumor, but not normal, endothelial cells. Test patterns arecompared to a database of reference biomaps that includes patternsobtained from the analysis of cells treated under environmentalconditions in which single components are removed, or with known drugsthat target specific pathways. Alternatively, reference biomaps aregenerated in the presence of genetic constructs that selectively targetspecific pathways. In this way, a database of reference biomaps isdeveloped that can reveal the contributions of individual pathways to acomplex response.

ANGIOGENESIS INHIBITORS

[0192] The present invention can be applied to the identification ofcompounds that inhibit or modulate angiogenesis. Pharmacologicmodulation of angiogenesis has applications to the treatment of cancer,where vascularization of tumors contributes to cancer growth; forinflammatory conditions such as arthritis where neovascularizationsupports inflammatory cell influx; wound healing; and others. A numberof biologically active agents are known to induce or promoteangiogenesis including VEGF, FGF, IL-8, IL-4, various extracellularmatrix components, etc., where at least 2, usually at least 3 of thesefactors may be used in an assay combination. Physiologically relevantstates in vivo are complex, containing combinations of factors and otherconditions. The environment of rheumatoid arthritis, in which angiogenicfactors are present in a proinflammatory environment, can bedistinguished from tumor environments that may be characterized byreduced oxygen and the presence of various growth factors in combinationwith a pro-angiogenic environment. Culture environments for endothelialcells that reflect these disease or physiological environments aredeveloped through an iterative process of (a) identifying factors thatare known to be expressed at the disease site. For example,vascularizing arthritis environments contain basic FGF and VEGF inaddition to TNF-α, IL-1, IL-6, IL-10, IL-15, MIP1β and MCP-1 (Qu, 1995,Lab Invest., 73:339; Koch, J. Immunol. 1994, 152:4149; Robinson, 1995,Clin. Exp. Immunol. 101:398; Thurkow, 1997, J. Pathol. 181:444; Suzuki,1999, Int. Immunol, 11:553). The disease environments of highlyvascularized tumors includes hypoxia, VEGF, fibrinogen and TGF-β(Senger, 1994 Invasion Metastasis, 95:385; Shweiki, 1992, Nature,359:843). The iterative process then (b) identifies a set of parametersthat includes those that are known to be differentially regulated by oneor more of the factors identified in (a), or parameters includingadhesion molecules, receptors, chemokines, etc., that are known to bedifferentially expressed by angiogenic endothelium at the disease sites.These may include the expression of functional forms of adhesionmolecules such as α_(v)β₃, VCAM, proteases, such as matrixmetalloproteinases, or other substances. The process then c) evaluatesthe effects of environments containing combinations of factors on theexpression of parameters on endothelial cells in vitro; and d) selectsconditions (factor composition, time course, concentration, etc.) thatresult in the pattern of expression of parameters that is representativeof the in vivo phenotype. Optimization of the final set of environmentalconditions and parameters is carried out by testing larger panels ofparameters under the different environmental conditions in vitro andselecting those that can discriminate between two or more environments,said environments differing by one or more individual environmentalcomponents. This procedure can be performed in a high throughput manner,and individual selected parameters can be confirmed by evaluating theexpression in vivo under normal and disease tissues. The goal of theabove process is the identification and selection of a minimal set ofparameters, each of which provides a robust readout, and that togetherenable discrimination of each environmental condition.

[0193] Once a panel of environments is identified, and an optimal set ofparameters is selected, cells are treated under each condition and adatabase of reference biomaps is developed. These include referencebiomaps from cells treated under environments that include known drugsthat target specific pathways, as well as reference biomaps from theanalysis of cells treated under environmental conditions in which singleor multiple components are removed. For example, for an assaycombination representing endothelial cells in a vascularizing arthritisenvironment, reference biomaps are developed from assay combinations inwhich single components (e.g. VEGF) might be removed. Reference biomapsare also generated from cells containing genetic constructs thatselectively target specific pathways. In this way, a database ofreference biomaps is developed that can reveal the contributions ofindividual pathways to a complex response.

[0194] With such a database, the invention provides for preferentialselection of drug compounds that inhibit angiogenic responses in complexenvironments. Such compounds would be identified by their ability toinduce a biomap consistent with inhibition of an angiogenic phenotype inthe presence of a complex environment. Compounds that selectively blockthe response to a single factor or component of the complex environment(e.g. FGF receptor signaling, etc.) would be revealed by a biomapconsistent with the response pattern in the absence of that factor (e.g.FGF, etc.)

[0195] The invention is also useful for screening compounds for druginteractions. Drug interactions can be problematic in cancer therapy.For example, while steroids control the edema that occurs with glioma,they also interfere with chemotherapy efficacy. Cytotoxic drugs form thebasis of many cancer therapies, thus interference with chemotherapyefficacy may offset any anti-tumor effects of angiogenesis inhibitors.Most cytotoxic drugs effect both normal and neoplastic cells, althoughat different concentrations, therefore, screening compounds in thepresence of cytotoxic drugs can be performed and reveal unexpectedinterference or beneficial synergies. Interactions between a cytotoxicdrug and any test compound would be detected by the observation ofbiomaps obtained in the presence of both drugs that are inconsistentwith additive effects.

MODULATORS OF BONE DEVELOPMENT

[0196] Modulation of bone development and remodeling has application forthe therapy of osteoporosis, atherosclerosis, and rheumatoid arthritis,all situations where undesired bone destruction, bone formation ormorphogenesis occurs. Bone-forming osteoblasts are derived from a commonprecursor in bone marrow that differentiates into osteoblasts oradipocytes depending on the differentiation environment. Factorsassociated with osteoblast development include estrogen, bonemorphogenic proteins and TGF-β. Differentiation of osteoblasts isassociated with the production of alkaline phosphatase, type I collagen,osteopontin and the ability to mineralize calcium. Factors associatedwith adipocyte development include FGF and glucocorticoids.Differentiation of adipocytes is associated with their production ofPPAR(2, lipoprotein lipase and leptin. Optimized culture environmentsare defined for the relevant disease or physiologic states as describedabove and a set of parameters that distinguish adipocyte and osteoblastdifferentiation are selected. For screening compounds for inhibitors ofosteoporosis, test compounds are screened for their ability to promoteosteoblast development in the relevant disease environment. For example,in the case of older women, that would include low estrogen levels; inthe case of autoimmune disease patients on long term glucocorticoidtherapy, the environment may contain dexamethasone, and so on.

[0197] Modulation of osteoclast development and function hasapplications for bone remodeling that occurs in rheumatoid arthritis.Osteoclasts develop from CD14+ monocytes. Factors that promoteosteoclast development include TRANCE (RANKL or osteoprotegrin ligand),TGF β and M-CSF. Rheumatoid arthritis environments also contain TNF-α,IL-1, IL-6, IL-10, IL-15, MIP1β and MCP-1 (Robinson, 1995, Clin. Exp.Immunol. 101:398; Thurkow, 1997, J. Pathol. 181:444; Suzuki, 1999, Int.Immunol, 11:553). Optimized culture environments are defined forosteoclasts or precursor CD14+ monocytes in pro-osteoclast developmentarthritis environment. A set of parameters is selected that identifiesosteoclasts in such an environment. Osteoclast function is associatedwith expression of calcitonin, vitronectin receptors, cathepsis k,carbonic anhydrase II, vacuolar (H(+)) ATPase, tartrate-resistant ATPaseand osteopontin. For screening compounds to identify inhibitors ofosteoclast development or function, active compounds are identified bytheir ability to inhibit osteoblast development in the relevant diseaseenvironment.

NEUROBIOLOGY APPLICATIONS A LZHEIMER'S DISEASE

[0198] A prominent feature of Alzheimer's disease patients is activatedglia (astrocytes and microglia) in close proximity to amyloid plaques.These cells express increased levels of Class II antigens,alpha-1-antichymotrypsin, IL-1β, S-100β and butyrylcholinesterase. Thedisease environment in Alzheimer's disease contains IL-1, IL-6 and theβ-amyloid peptide 1-42.

[0199] Regulators of Hematopoiesis

[0200] Mesenchymyl stem cell cultures can be provided with environmentsleading to fibroblastic, osteoblastic, or adipocyte differentiation,each associated with unique patterns of cell surface and secretedmolecule expression defining these cellular states. A set of parametersthat identifies various lineages of hematopoietic cells (e.g. erythroid,myeloid, T versus B, NK, etc.) are selected. Compounds that alter thedifferentiation of selected cell types are selected by their ability toproduce biomaps characteristic of that population.

KITS

[0201] For convenience, the systems of the subject invention may beprovided in kits. The kits could include the appropriate additives forproviding the simulation, optionally include the cells to be used, whichmay be frozen, refrigerated or treated in some other manner to maintainviability, reagents for measuring the parameters, and software forpreparing the biomap. The factors will be selected that in conjunctionwith the cells would provide the desired physiological state simulatingthe in vivo situation. The factors could be a mixture in the appropriateproportions or provided individually. For example, IL-1, TNF-α, andIFN-γ would be combined as a powder to be measured for addition to thecell medium and labeled antibodies to parameters, such as ICAM-1, VCAM-1and E-selectin, in conjunction with second capture antibodies or usingantibodies for homogeneous assays, where another reagent is present. Thesoftware will receive the results and create a biomap and can includedata from other assay combinations for comparison. The software can alsonormalize the results with the results from a basal culture and/or thebasal culture including the factors.

EXPERIMENTAL EXAMPLE 1 REGULATORS OF ENDOTHELIAL CELL RESPONSES TOINFLAMMATION

[0202] The present invention is useful for identifying regulators ofinflammation using human endothelial cells as an indicator cell type. Aset of assay combinations that reproduces aspects of the response of theendothelial cells to different types of inflammatory processes isdeveloped in vitro.

[0203] Primary human umbilical vein endothelial cells (HUVEC) are used.Other cells that may replace HUVEC in the screen include primarymicrovascular endothelial cells, aortic or arteriolar endothelial cellsor endothelial cell lines such as EAhy926 or E6-E7 4-5-2G cells or humantelomerase reverse transcriptase-expressing endothelial cells (Simmons,J. Immunol., 148:267, 1992; Rhim, Carcinogenesis 19:673, 1998; Yang, J.Biol. Chem. 274:26141, 1999). 2×10⁴ cells/ml are cultured to confluencein EGM-2 (Clonetics). Other media that may replace EGM-2 include EGM(Clonetics) and Ham's F12K medium supplemented with 0.1 mg/ml heparinand 0.03-0.05 mg/ml endothelial cell growth supplement (ECGS) and 10%FBS, or medium M199 (Life Technologies, Inc.) containing 20% fetalbovine serum and 2 ng/ml basic fibroblast growth factor (Jaffe, J. Clin.Invest. 52:2745, 1973; Hoshi, PNAS 81:6413, 1984). The diseaseenvironment present in chronic inflammatory diseases, such as Crohn'sdisease, differs from the normal condition by increased presence ofmultiple biologically active agents including IL-1, TNF-α, and IFN-γ(Woywodt, 1994; Kakazu, 1999). Other biologically active agents that maybe increased in chronic inflammatory disease environments include IL-4,IL-6, IL-8, IL-12, IL-13, IL-18, TGFbeta, and histamine, as well asactivated leukocytes and their products (Daig, 1996, Gut 38:216;Woywodt, 1994, Eur. cytokine Netw. 5:387; Kakazu, 1999 Am J.Gastroenterol. 94:2149; Pizarro, 1999, J. Immunol. 162:6829; Monteleone,1999, J. Immunol. 163:143; McClane, 1999 J Parenter Enteral Nutr 23:S20;Beck, 1999, Inflam. Bowel Dis. 5:44). Optimized assay combinations willcontain at least two, and preferably three, four or more of thesebiologically active agents. Concentrations of agents are standardaccording to the literature, typically at physiologic concentrations.Concentrations may also be determined experimentally as the amountrequired to saturate the relevant receptor. A useful feature of thepresent invention is that combinatorial effects of multiple factors areobserved over wide ranges of factor concentrations. Based on the factorsincluded in an assay combination, a set of parameters for including in abiomap are selected.

[0204] Selection of parameters is based on the following factors: 1)parameters that are modulated in vivo in the disease environment orcondition; 2) parameters that are modulated by one of the components inthe assay combination; 3) parameters that are modulated by more than oneof the components in the assay combination; 4) parameters that aremodulated by the combined action of two or more components in the assaycombination; 5) parameters that participate in the disease process, suchas validated disease targets; 6) cell surface and secreted molecules.Preferred parameters are functional and are downstream within signalingpathways, so as to provide information on effects of multiple pathways.For assay combinations containing the factors TNFα, IFN-γ and IL-1,parameters examined and chosen by these criteria include ICAM-1 (CD54),VCAM-1 (CD106), E-selectin (CD62E), IL-8, HLA-DR and MIG (CLCX9). Otherparameters of interest for including in a Biomap include: IP-10,Eotaxin-1, Eotaxin-3, MCP-1, RANTES, Tarc, CD31, alphavbeta3, andP-selectin (CD62P). Parameters examined but not selected include: CD34,CD40, CD9, CXCR2, CD95, fibronectin, HLA-ABC, GROalpha, MCP-4, TAPA-1,alphaVbeta5, VE-Cadherin, CD44, von Willebrand factor, CD141, 142, 143,and CD151. Parameters are not selected for inclusion in a biomap for thefollowing reasons: redundancy, function of parameter is not associatedwith disease pathology, function is upstream in a signaling pathway,parameter is not modulated in response to factors, modulation is notrobust or reproducible. Cell death in inflammation, involved for examplein cellular remodeling in healing, as well as the consequences oftoxicity, involves apoptosis. Parameters of interest also includeparameters indicative of cell damage and apoptosis including releasedcytoplasmic lactate dehydrogenase (LDH) or mitochondrial cytochrome c,appearance of APO2.7 epitope or active caspase-3 (Zhang, J. Immunol.,157:3980, 1996; Bussing, Cytometry 37:133, 1999). Parameters indicativeof cell proliferation are also of interest and include Ki-67 and PCNA(Landberg, Cytometry, 13:230, 1992).

[0205] Strategies for optimizing the parameter set include: selectingonly one of any group of parameters that are co-regulated under allassay combinations; preferentially selecting parameters that arefunctionally relevant to the disease process; preferentially selectingparameters that give robust and reproducible results in multiple assays,or reflect cellular toxicity etc. In the present example, whereas bothIP-10 and MIG are co-regulated under the assay conditions described,detection of MIG by the cell-based ELISA as described above is morerobust, therefore MIG was preferentially included in the optimized setof parameters. For parameter set optimization, additional parameters maybe added to the initial parameter set to distinguish assay combinationsthat result in cellular de-adhesion, toxicity or other activity.Microscopic observation can identify cellular de-adhesion, while releaseof cytoplasmic substances, such as lactate dehydrogenase, can bemeasured as an indication of toxicity. For example, CD31 is anendothelial cell adhesion molecule that participates in cell-celladhesion and complete loss of CD31 expression in an assay indicates lossof cells from the plate. Therefore, CD31 is a useful parameter formonitoring cellular de-adhesion.

[0206] The experiments provided in FIGS. 1A-1C illustrate the usefulnessof the present invention in compound screening applications. FIG. 1Ashows the readout patterns from confluent cultures of HUVEC incubatedwith either of TNF-α (5 ng/ml), IFN-γ (100 ng/ml) or IL-1 (1 ng/ml) orbasal medium for 24 hours. After 24 hours, cultures are washed andevaluated for the presence of the parameters ICAM-1 (1), VCAM-1 (2),E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7) by cell-basedELISA as described (Melrose, J. Immunol. 161:2457, 1998). For this,plates are blocked with 1% Blotto for 1 hr, and treated with primaryantibodies (obtained from Pharmingen and Becton Dickinson) at 1 ng/mlfor 2 hr. After washing, secondary peroxidase-conjugated anti-mouse IgGantibody (Promega) at 1:2500 is applied for 45 min. After washing, TMBsubstrate (Kierkegaard & Perry) is added and color developed.Development is stopped by addition of H₂SO₄ and the absorbance at 450 nm(subtracting the background absorbance at 600 nm) is read with aMolecular Dynamics plate reader. The relative expression levels of eachparameter are indicated by the OD at 450 nm shown along the y-axis. Themean +/−SD from triplicate samples is shown. The assay combinationsshown in FIG. 1 are useful in screening compounds that modulate TNF-α,IL-1 and IFN-γ signaling pathways, however, compounds must be evaluatedseparately in all three assay combinations to identify compounds thatselectively modulate one or more of these pathways. In addition,compounds that selectively modulate combinatorial effects of thesepathways cannot be distinguished.

[0207] An assay combination with improved usefulness is described inFIG. 1B. FIG. 1B shows the readout patterns from confluent cultures ofHUVEC cells treated with TNF-α (5 ng/ml), IFN-γ (100 ng/ml), TNF-α (5ng/ml)+IFN-γ (100 ng/ml) or base media. After 24 hours, cultures arewashed and evaluated for the presence of the parameters ICAM-1 (1),VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7)by cell-based ELISA performed as described in FIG. 1 and are reported asthe OD at 450 nm in FIG. 2. The mean +/−SD from triplicate samples areshown. * indicates p<0.05 comparing results obtained with the twoseparate conditions. As shown in FIG. 2, HUVEC cultured with TNF-α for24 hours express increased levels of cell surface ICAM-1, VCAM-1, andE-selectin as measured by cell-based ELISA. HUVEC cultured with IFN-γfor 24 hours express increased levels of ICAM-1, HLA-DR and MIG. HUVECcultured in the presence of both TNF-α and IFN-γ for 24 hours produce acombined phenotype where HUVEC express increased levels of ICAM-1,VCAM-1, E-selectin, HLA-DR and MIG. This phenotype is more similar tothe in vivo phenotype of endothelial cells in chronic inflammation andmoreover reflects the stimulation of two different known pathways ofinterest in regulation of inflammatory processes. Concentrations ofTNF-α and IFN-γ employed and length of exposure are standard accordingto the literature. Concentrations and exposure length are also testedexperimentally and conditions chosen to achieve an endothelial cellphenotype displaying multiple features of endothelial cells in chronicinflammatory diseases (e.g increased expression of ICAM-1, VCAM-1,E-selectin as well as HLA-DR and MIG). However, a particularly usefulfeature of the invention is that the combined phenotype is observed overa wide range of concentrations of the individual biologically activefactors. The results in FIG. 1B demonstrate how an assay combinationcontaining both TNF-α and IFN-γ is useful in screening for compoundsthat block either the TNF-α or IFN-γ signaling pathways, andfurthermore, can be used to distinguish compounds that modulatecombinatorial effects of these pathways.

[0208] Inclusion of additional biologically active factors furtherimproves the usefulness of the screens provided in the presentinvention. FIG. 1C shows the readout patterns from confluent cultures ofHUVEC cells treated with TNF-α (5 ng/ml)+IFN-γ (100 ng/ml) or TNF-α (5ng/ml)+IFN-γ (100 ng/ml)+IL-1 (1 ng/ml). After 24 hours, cultures arewashed and evaluated for the presence of the parameters ICAM-1 (1),VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7)by cell-based ELISA performed as described in FIG. 1 and are reported asthe OD at 450 nm. The mean +/−SD from triplicate samples are shown. *indicates p<0.05 comparing results obtained with the two separateconditions. Addition of IL-1 to the assay combination containing TNF-αand IFN-γ results in increased levels of E-selectin and IL-8 (shown inFIG. 1B), in addition to the increased levels of ICAM-1, VCAM-1, HLA-DRand MIG. E-selectin and IL-8 are particularly correlated with diseasestage in chronic inflammatory diseases, including inflammatory boweldisease (MacDermott, 1999, J. Clin. Immunol. 19:266; Koizumi, 1992,Gastroenterology 1992103:840). Thus an assay combination containingIL-1, TNF-α and IFN-γ represents an optimized assay combination. Thisassay combination is useful for screening for compounds that modulateaspects of IL-1, TNF-α or IFN-γ signaling pathways. In particular, itprovides a useful screen for selecting compounds that are active when aparticular target pathway may be modified by the activity of otherpathways or when the target is not known.

[0209] In subsequent panels one or more of IL-4, IL-6, IL-8, IL-12,IL-13, IL-18, TGFbeta, and histamine are applied; and/or neutralizingantibodies to autocrine factors such as IL-6, IL-1 and IL-8. Standardconcentrations of agents are employed as described in the literature.Based on the factors selected, a set of parameters for including in abiomap is selected.

[0210] Database of readout response patterns. A database of referencebiomaps is compiled for the optimized assay combination and parameterset of the example described in FIG. 1C. These reference biomaps aredeveloped from assay combinations in which specific modifications of theoptimized assay combination are made. These modifications included: 1)elimination of one or more assay combination components, 2) addition ofcompounds or interventions to the assay combination. Biologicalresponses, particularly responses in primary human cells can displaysignificant variability from day to day and from donor to donor. Oneimportant aspect of the present invention is that while absolute amountsof parameters can vary substantially between assays, combinatorialresponses provide for less variability and the process of normalizationto produce a biomap provides cellular activity profiles that are robustand reproducible.

[0211]FIG. 2A shows a set of reference biomaps developed from assaycombinations in which one or more of the cytokines, IL1, TNF-α or IFN-γis eliminated. For each reference assay combination, the selectedparameters are measured and the resulting biomaps developed from thedata are compared. FIG. 2A shows how measuring the levels of theparameters ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5),HLA-DR (6), and MIG (7), by cell-based ELISA under each of these assaycombinations, results in different reference biomaps for each assaycombination. The set of parameter measurements under each of theseconditions comprises a reference biomap to which test patterns can becompared. FIG. 2B shows a visual representation of this data, where themeasurement obtained for each parameter is classified according to itsrelative change from the value obtained in the optimized assaycombination (containing IL-1+TNF-α+IFN-γ), and represented by shadedsquares. For each parameter and assay combination, the square is coloredlight gray if the parameter measurement is unchanged (<20% above orbelow the measurement in the first assay combination (IL-1+TNF-α+IFN-γ))or p>0.05, n=3; white/gray hatched indicates that the parametermeasurement is moderately increased (>20% but <50%); white indicates theparameter measurement is strongly increased (>50%); black/gray hatchedindicates that the parameter measurement is moderated decreased (>20%but <50%); black indicates that the parameter measurement is stronglydecreased (>50% less than the level measured in the first assaycombination).

[0212]FIG. 2C shows an alternative visual representation of the set ofreference biomaps whereby individual parameter readouts are compared byhierarchical cluster analysis. For this, regression analysis isperformed on reference biomaps and correlation coefficients are used incluster analysis. The clustering relationships can be representedvisually, for example, as a tree in which related biomaps are on commonbranches, and the distance between patterns on the tree reflects theextent of differences in the biomaps. FIG. 2C shows how the biomapsderived from assay combinations containing TNF-α and/or IL1 are easilydistinguished from those derived from assay combinations containingIFN-γ or the combination of IFN-γ and TNF-α and/or IL-1. Applyingweighting factors to individual parameter readouts allows the biomapanalysis to sufficiently distinguish particular signaling pathways ofinterest. A significant aspect of the invention is the selection of aset of parameters and assay combinations that can optimally distinguishmultiple pathways of interest. Active compounds are chosen on the basisof their ability to alter the resulting biomap when included in aselected assay combination. Such alteration may include returning thelevels of one or more parameters to their levels in the basal condition,or otherwise altering the cellular responses, particularly when suchalterations reflect changes towards a desirable cellular state.

[0213] An inhibitor of TNF-α is an active compound in the optimizedassay combination described above. Addition of neutralizing anti-TNF-αantibodies to this assay combination results in reduced expressionlevels of ICAM-1, VCAM-1, E-selectin, IL-8, and MIG, and increasedexpression levels of CD31(FIG. 3A). Confluent cultures of HUVEC cellsare treated with TNF-α (5 ng/ml)+IFN-γ (100 ng/ml)+IL-1 (1 ng/ml) in thepresence or absence of neutralizing anti-TNF-α or control antibody (Goatanti-IgG). After 24 hours, cultures are washed and evaluated for thecell surface expression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8(4), CD31 (5), HLA-DR (6) and MIG (7) by cell-based ELISA performed asdescribed in FIG. 1. In FIG. 3A, the relative expression of eachparameter is shown along the y-axis as average value of the OD measuredat 450 nm of triplicate samples. The mean +/−SD from triplicate samplesare shown. * indicates p<0.05 comparing results obtained with anti-TNF-αto the control.

[0214]FIG. 3B, is a color-coded representation of the biomaps developedfrom the data shown in A. For each parameter and assay combination, thesquare is colored light gray if the parameter measurement is unchanged(<20% above or below the measurement in the first assay combination(IL-1+TNF-α+IFN-γ)) or p>0.05, n=3; white/gray hatched indicates thatthe parameter measurement is moderately increased (>20% but <50%); whiteindicates the parameter measurement is strongly increased (>50%);black/gray hatched indicates that the parameter measurement is moderateddecreased (>20% but <50%); black indicates that the parametermeasurement is strongly decreased (>50% less than the level measured inthe first assay combination).

[0215] Inhibitors of NFεB, MAP kinases and non-steroidalantiinflammatory drugs are active compounds in the optimized assaycombination described above. FIG. 4A shows results of assaying confluentcultures of HUVEC cells treated with TNF-α (5 ng/ml)+IFN-γ (100ng/ml)+IL-1 (1 ng/ml) in the presence or absence of (A) 10 μM NHGA, 200μM PDTC or 9 μM PD098059 or (B) 125-500 μM ibuprofen. Compounds aretested at the highest concentration at which they are soluble, and donot result in cellular toxicity or loss of cells from the plate. After24 hours, cultures are washed and evaluated for the cell surfaceexpression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31(5), HLA-DR (6) and MIG (7) by cell-based ELISA performed as describedin FIG. 1. A color-coded representation of the biomaps developed fromthe data is shown. For each parameter and assay combination, the squareis colored light gray if the parameter measurement is unchanged (<20%above or below the measurement in the first assay combination(IL-1+TNF-α+IFN-γ)) or p>0.05, n=3; white/gray hatched indicates thatthe parameter measurement is moderately increased (>20% but <50%); whiteindicates the parameter measurement is strongly increased (>50%);black/gray hatched indicates that the parameter measurement ismoderately decreased (>20% but <50%); black indicates that the parametermeasurement is strongly decreased (>50% less than the level measured inthe first assay combination).

[0216] In the present example, FIG. 4A shows how addition of the NFκBinhibitors nordihydroguaiaretic acid (NHGA) (Brennen, Biochem.Pharmacol., 55:965, 1998) or pyrrolidine dithiocarbamate (PDTC) (Boyle,Circulation, 98, (19 Suppl):11282, 1998) to the optimized assaycombination results in altered biomaps that are distinct from thealtered biomaps obtained with the p42/44 MAP kinase inhibitor, PD098059(Milanini, J. Biol. Chem. 273:18165, 1998). Active compounds that actwith a similar mechanism of action as NHGA and PDTC will give a biomapthat can be distinguished from active compounds that act with a similarmechanism of action as PD098059.

[0217] Obtaining biomaps from drug compounds tested at differentconcentrations also expands the usefulness of the database. In thepresent example, ibuprofen gives visually biomaps when tested at 500,250 and 125 μM, as shown in FIG. 4B, although regression analysisindicates they are highly related (correlation coefficients derived fromthe primary data range between 0.96-0.99).

[0218] Reference biomaps from assay combinations that include known drugcompounds, agents, or with other specific modifications are developedfor inclusion in a database. Biomaps from these assay combinations aredeveloped so as to expand the usefulness of the database. Table 1 showsa list of agents or specific modifications evaluated, includingN-acetylcysteine (Faruqui, Am. J. Physiol. 273(2 Pt 2):H817, 1997), thecorticosteroids dexamethasone and prednisolone, echinacea, AA861 (Lee,J. Immunol. 158, 3401, 1997), apigenin (Gerritsen, Am. J. Pathol.147:278, 1995), nordihydroguaiaretic acid (NHGA) (Brennen, Biochem.Pharmacol., 55:965, 1998), phenylarsine oxide (PAO) (Dhawan, Eur. J.Immunol. 27:2172, 1997), pyrrolidine dithiocarbamate (PDTC) (Boyle,Circulation, 98, (19 Suppl):11282, 1998), PPM-18 (Yu, Biochem. J.,328:363, 1997), the non-steroidal anti-inflammatory drug (NSAID)buprofen, SB 203580, PD098059 (Milanini, J. Biol. Chem. 273:18165,1998), AG126 (Novogrodsky, Science 264, 1319, 1994), and neutralizinganti-TNF-α antibody. Color-coded representations of the resultingbiomaps are shown. Confluent cultures of HUVEC cells are treated withTNF-α (5 ng/ml)+IFN-γ (100 ng/ml)+IL-1 (1 ng/ml) in the presence orabsence of agents or buffers at the concentrations indicated in Table 1.Compounds are obtained from commercial sources and prepared in asuitable buffer (water, base media, DMSO, methanol or ethanol). After 24hours, cultures are washed and evaluated for the cell surface expressionof ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR(6) and MIG (7) by cell-based ELISA performed as described in FIG. 1. Acolor-coded representation of the resulting biomaps developed from thedata is shown. For each parameter and assay combination, the square iscolored light gray if the parameter measurement is unchanged (<20% aboveor below the measurement in the control assay combination(IL-1+TNF-α+IFN-γ)) or p>0.05, n=3; white/gray hatched indicates thatthe parameter measurement is moderately increased (>20% but <50%); whiteindicates the parameter measurement is strongly increased (>50%);black/gray hatched indicates that the parameter measurement ismoderately decreased (>20% but <50%); black indicates that the parametermeasurement is strongly decreased (>50% less than the level measured inthe first. Control assay combinations for each agent include anappropriate concentration of the diluent buffer. TABLE 1 Referencebiomaps. Readout Parameters Inhibitor Class UID Compound Conc. Units

Antioxidant 181 N-acetylcysteine 5.00 μM

Antioxidant 182 N-acetylcysteine 2.50 μM

Antioxidant 183 N-acetylcysteine 1.25 μM

Antioxidant 184 N-acetylcysteine 1.25 μM

Corticosteroid 717 Dexamethazone 12.50 μM

Corticosteroid 716 Dexamethazone 6.25 μM

Corticosteroid 715 Dexamethazone 3.10 μM

Corticosteroid 301 Dexamethazone 2.00 μM

Corticosteroid 302 Dexamethazone 1.00 μM

Corticosteroid 303 Dexamethazone 0.50 μM

Corticosteroid 241 Prednisolone 160.00 μM

Corticosteroid 242 Prednisolone 160.00 μM

Corticosteroid 243 Prednisolone 80.00 μM

Corticosteroid 244 Prednisolone 40.00 μM

Natural Product 91 Echinacea 2.27 %

Natural Product 94 Echinacea 2.27 %

Natural Product 92 Echinacea 1.13 %

Natural Product 93 Echinacea 0.57 %

NF_(K)B 4 AA861 20.00 μM

NF_(K)B 5 AA861 20.00 μM

NF_(K)B 6 AA861 20.00 μM

NF_(K)B 701 AA861 20.00 μM

NF_(K)B 19 Apigenen 8.10 μM

NF_(K)B 20 Apigenen 6.00 μM

NF_(K)B 21 Apigenen 5.00 μM

NF_(K)B 202 Nordihydroguaiaretic acid (NHGA) 10.00 μM

NF_(K)B 203 Nordihydroguaiaretic acid (NHGA) 10.00 μM

NF_(K)B 204 Nordihydroguaiaretic acid (NHGA) 10.00 μM

NF_(K)B 719 Nordihydroguaiaretic acid (NHGA) 6.00 μM

NF_(K)B 205 Nordihydroguaiaretic acid (NHGA) 5.00 μM

NF_(K)B 718 Nordihydroguaiaretic acid (NHGA) 0.63 μM

NF_(K)B 720 PAO 50.00 μM

NF_(K)B 231 PDTC 200.00 μM

NF_(K)B 233 PDTC 200.00 μM

NF_(K)B 234 PDTC 200.00 μM

NF_(K)B 725 PDTC 100.00 μM

NF_(K)B 726 PDTC 100.00 μM

NF_(K)B 235 PDTC 100.00 μM

NF_(K)B 232 PDTC 50.00 μM

NF_(K)B 724 PDTC 50.00 μM

NF_(K)B 236 PDTC 50.00 μM

NF_(K)B 728 PPM-18 2.50 μM

NF_(K)B 727 PPM-18 2.00 μM

NF_(K)B 735 PPM-18 2.00 μM

NSAID 131 Ibuprofen 500.00 μM

NSAID 132 Ibuprofen 500.00 μM

p38 MAPK 730 SB 203580 80.00 μM

p38 MAPK 729 SB 203580 40.00 μM

p42/44 MAPK 221 PD098059 18.70 μM

p42/44 MAPK 222 PD098059 9.30 μM

p42/44 MAPK 223 PD098059 9.30 μM

p42/44 MAPK 224 PD098059 9.00 μM

p42/44 MAPK 723 PD098059 9.00 μM

p42/44 MAPK 225 PD098059 4.60 μM

p42/44 MAPK 722 PD098059 2.25 μM

p42/44 MAPK 721 PD098059 0.56 μM

Tyr Kinase 733 AG126 25.00 μM

Tyr Kinase 702 AG126 25.00 μM

Tyr Kinase 734 AG126 25.00 μM

Antibody 712 Anti-TNF 5.00 μg/ml

Antibody 713 Anti-TNF 5.00 μg/ml

Antibody 711 Anti-TNF 4.00 μg/ml

Antibody 710 Anti-TNF 1.67 μg/ml

Antibody 709 Anti-TNF 0.55 μg/ml

Antibody 708 Anti-TNF 0.40 μg/ml

Antibody 707 Anti-TNF 0.04 μg/ml

Antibody 714 Anti-TNF-R (Act) 5.00 μg/ml

N/A 520 Control

N/A 521 Control

N/A 522 Control

N/A 523 Control

N/A 524 Control

N/A 525 No IL1

N/A 526 No IL1

N/A 527 No IL1

N/A 531 No TNF

N/A 532 No TNF

N/A 533 No TNF

N/A 515 No IL1IFNg

N/A 516 No IL1IENg

N/A 517 No IL1IFNg

N/A 518 No IL1IENg

N/A 519 No IL1IFNg

N/A 510 No TNFIFNg

N/A 511 No TNFIFNg

N/A 512 No TNFIFNg

N/A 513 No TNFIFNg

N/A 514 No TNFIFNg

N/A 505 No IL1TNF

N/A 506 No IL1TNF

N/A 507 No IL1TNF

N/A 508 No IL1TNF

N/A 509 No IL1TNF

N/A 500 No IL1TNFIFNg

N/A 501 No IL1TNFIFNg

N/A 502 No IL1TNFIFNg

N/A 503 No IL1TNFIFNg

N/A 504 No IL1TNFIFNg

[0219]FIG. 4C shows a visual representation of how these referencebiomaps can be compared by pattern similarity and cluster analysis.Readout patterns are analyzed by hierarchical clustering techniques, andare visualized as a tree diagram in which a) each terminal branch pointrepresents the readout pattern from one assay combination in oneexperiment; b) the length of the vertical distance from the upperhorizontal line (no change and control patterns) to the termini arerelated to the extent of difference in the readout pattern from thecontrol environment pattern; and c) the distance along the branches fromone terminal pattern value to another reflects the extent of differencebetween them. Similar patterns are thus clustered together.

[0220] Compounds that inhibit the NFκB pathway, such as the5-lipoxygenase inhibitors M861 and nordihydroguaiaretic acid (NHGA)(Lee, J. Immunol. 158, 3401, 1997), pyrrolidine dithiocarbamate (PDTC)(Boyle, Circulation 98:(19 Suppl):11282, 1998), PPM-18, a chemicallysynthesized naphthoquinone derivative (Yu, Biochem. J., 328:363, 1997)and the flavenoid apigenin (Gerritsen, Am. J. Pathol. 147:278, 1995),have similar reference biomaps and cluster together. Thecorticosteroids, dexamethasone and prednisolone also yield a set ofrelated reference biomaps that are distinct from those of NFκB pathwayinhibitors.

[0221] An important feature of biomap analysis is how biomaps resultingfrom different concentrations of active agents, although they differfrom one another (see FIG. 4C), remain clustered together in the clusteranalysis. This can be seen in FIG. 4C where the biomaps that result fromtesting PD098059 at different concentrations remain in the same cluster(indicating their similarity with one another), although biomapsresulting from testing PD098059 at higher concentrations are found inthe lower branches of the cluster, indicating higher degree ofdifference (lower correlation coefficient) from the biomaps resultingfrom no intervention or inactive agents. Thus biomap analysis is usefulfor distinguishing the mode of action of a variety of compounds.

[0222] This example demonstrates that the biomaps are useful indistinguishing the mode of action of candidate compounds, so as to knowwhether combinations of candidate compounds act on the same pathway ordifferent pathways, their combined effect on parameter levels andwhether they provide synergy or act in an antagonistic way.

[0223] These assay combinations are highly useful for testing a largenumber of compounds or agents with many different or unknown mechanismsof action. This procedure balances the desirability of a screening assaythat provides in depth information, with the advantages of an assay thatis also amenable for scale-up high throughput screening. The assaycombinations described are useful for general screening for compoundswith anti-inflammatory or proinflammatory activity. Assay combinationstailored for specific inflammatory diseases are developed by alteringthe combination of input biologically active agents. For example,specific assay combinations useful for inflammatory diseases that aremore Th2-like in nature, such as asthma or allergy should includeadditional agents, such as IL-4 or IL-13, that are preferably found inthose disease conditions, and so forth.

EXAMPLE 2 MULTIPLEX ASSAY COMBINATIONS FOR DISTINGUISHING MECHANISM OFACTION

[0224] The following example demonstrates the utility of the inventionin identification of the mechanism of action of a test compound orintervention identified in the optimized assay combination of Example 1.This assay combination is included in a panel that contains specific andtargeted alterations. A neutralizing antibody to TNF-α was selected as atest agent, as it is active when tested in the optimized primary assaycombination of Example 1 (FIG. 3A). When the test agent is evaluated inthe panel of assay combinations, it can be determined if the activecompound is acting on a component(s) unique to one receptor-stimulatedpathway, or on a common pathway component or pathway activity. Theneutralizing antibody to TNF-α as a test agent evaluated in these assaycombinations alters the biomap, as shown in FIG. 3B.

[0225] Confluent cultures of HUVEC cells are treated with TNF-α (5ng/ml), IFN-γ (100 ng/ml), IL-1 (20 ng/ml), the combination ofTNF-α+IFN-γ+IL-1, or media (no cytokine) in the presence or absence ofneutralizing anti-TNF-α, 20 μM AA861 or 10 μM NHGA. After 24 hours,cultures are washed and evaluated for the cell surface expression ofICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), and MIG (5) bycell-based ELISA performed as described in FIG. 1. A color-codedrepresentation of the resulting biomaps derived from the data is shownin FIG. 5, coded as described in FIG. 2B.

[0226] These data demonstrate expression of the biomap from the assaycombination containing TNF-α alone is altered, but not the biomap in theassay combinations that contain IL-1 or IFN-γ alone. This resultdemonstrates that the test agent acts on the TNF-α pathway but not onthe IL-1 or IFN-γ pathways. FIG. 5 also shows the test compound isdistinguished from active compounds that target multiple cytokinesignaling pathways, such as the NFκB inhibitors, NHGA and M861.

[0227] The mechanism of action of the test agent is accomplished whenidentical biomaps are obtained from assay combinations containing thetest agent and assay combinations generated from known specificalterations of the assay combination. Eliminating the cytokine TNF-αfrom the primary assay combination results in the same biomap as theassay combination containing the test agent, the neutralizing TNF-αantibody.

[0228] Confirmation is performed by evaluating the test agent in assaycombinations that include both physiologic and alternative pathwayactivators. Confluent cultures of HUVEC cells are treated with TNF-α (5ng/ml), IL-1 (20 ng/ml), an activating antibody against the TNF-αreceptor p55, or media. After 24 hours, cultures are washed andevaluated for the cell surface expression of ICAM-1 (1), VCAM-1 (2),E-selectin (3), CD31 (4), and MIG (5) by cell-based ELISA performed asdescribed in FIG. 1. A color-coded representation of the resultingbiomap, prepared from the data is shown in FIG. 6, coded as described inFIG. 2B.

[0229]FIG. 6 shows that among the physiologic and alternative activatorsof the TNF-α pathway, the biomaps resulting from cultures containingeither IL-1 or an activating antibody to p55 are not sensitive to thetest agent, whereas the biomap resulting from cultures containing TNF-αis sensitive. As TNF-α is the most upstream component of the TNF-αpathway that is sensitive to the test agent, it is involved in thetarget pathway step of the test agent.

EXAMPLE 3 ANALYSIS IN MULTIPLEX ASSAY COMBINATIONS FOR IDENTIFYINGMECHANISM OF ACTION

[0230] The following example demonstrates the usefulness of the presentinvention for identification of mechanism of action of a test agentselected as an active agent. A recombinant fusion protein containing theextracellular domains of the p55 TNF-α-receptor fused to immunoglobulinFc domain (p55-Fc fusion protein) is selected as an active compound whentested in the optimized assay combination of Example 1 (FIG. 7A).

[0231] Confluent cultures of HUVEC cells are treated with TNF-α (5ng/ml)+IFN-γ (100 ng/ml)+IL-1 (20 ng/ml) in the presence or absence ofp55-Fc (50 ng/ml). After 24 hours, cultures are washed and evaluated forthe cell surface expression of ICAM-1 (1), VCAM-1 (2), E-selectin (3),CD31 (4), and MIG (5) by cell-based ELISA performed as described inFIG. 1. The relative expression of each parameter is shown in FIG. 7Aalong the y-axis as average value of the OD measured at 450 nm oftriplicate samples. The mean +/−SD from triplicate samples are shown. *indicates p<0.05 comparing results obtained with p55-Fc to the control.

[0232] In FIG. 7B, confluent cultures of HUVEC cells are treated withTNF-α (5 ng/ml), IFN-γ (100 ng/ml), IL-1 (20 ng/ml), the combination ofTNF-α+IFN-γ+IL-1, or media in the presence or absence of p55-Fc. After24 hours, cultures are washed and evaluated for the cell surfaceexpression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), and MIG(5) by cell-based ELISA performed as described in FIG. 1. A color-codedrepresentation of the resulting biomaps prepared from the data is shownin FIG. 7B, coded as described in FIG. 2B.

[0233] In FIG. 7C, confluent cultures of HUVEC cells are treated withTNF-α (5 ng/ml), IL-1 (20 ng/ml), an activating antibody against theTNF-α receptor p55, or media. After 24 hours, cultures are washed andevaluated for the cell surface expression of ICAM-1 (1), VCAM-1 (2),E-selectin (3), CD31 (4), and MIG (5) by cell-based ELISA performed asdescribed in FIG. 1. A color-coded representation of the resultingbiomaps prepared from the data is shown in FIG. 7C, coded as describedin FIG. 2B.

[0234] The p55-Fc fusion protein as a test agent evaluated in theseassay combinations, alters the biomap, as shown in FIG. 7B. The biomapin the assay combination containing TNF-α alone is altered, but not thebiomap in the assay combinations that contain IL-1 or IFN-γ alone. Thisresult demonstrates that the test agent acts on the TNF-α pathway butnot on the IL-1 or IFN-γ pathways.

[0235]FIG. 7C shows that among the physiologic and alternativeactivators of the TNF-α pathway, the biomap from IL-1 is not sensitiveto the test agent, whereas the biomap from TNF-α or an activatingantibody to the p55 is sensitive to the test agent. As theTNF-α-receptor p55 is the most upstream component of the TNF-α pathwaythat is sensitive to the test agent, it is a component of the targetstep of the test agent.

EXAMPLE 4 ANALYSIS IN MULTIPLEX ASSAY COMBINATIONS FOR IDENTIFYINGMECHANISM OF ACTION

[0236] The following example demonstrates the usefulness of the presentinvention for identification of mechanism of action of test agents thathave proinflammatory activities. An activating antibody toTNF-α-receptor p55 (Act-anti-p55) is an active compound when tested inan assay combination containing confluent HUVEC cultured in a basalmedium for 24 hours (FIG. 8, “no cytokine” assay combination), sinceAct-anti-p55 alters the biomap of this assay combination resulting inincreased levels of the readout parameters ICAM-1 (1), E-selectin (2)and VCAM-1 (3), and reduced levels of the readout parameter CD31 (4).

[0237] For identifying the mechanism of action and determining thecellular target, the test compound is evaluated in secondary or“decoding” assay combinations. These combinations contain the test agentas well as known regulators of the modulated parameters. For theparameters ICAM-1, VCAM-1 and E-selectin, known modulators include IL-1and TNF-α (ICAM-1, VCAM-1 and E-selectin); and IFN-γ (ICAM-1 andVCAM-1).

[0238] Confluent cultures of HUVEC cells are treated with TNF-α (5ng/ml), IFN-γ (100 ng/ml), IL-1 (20 ng/ml), the combination ofTNF-α+IFN-γ+IL-1, or media in the presence or absence of Act-anti-p55.After 24 hours, cultures are washed and evaluated for the cell surfaceexpression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), and MIG(5) by cell-based ELISA performed as described in FIG. 1. A color-codedrepresentation of the resulting biomaps prepared from the data is shownin FIG. 8, coded as described in FIG. 2B.

[0239]FIG. 8 shows that the test agent alters the biomaps derived ofassay combinations containing IL-1 or IFN-γ, but not the biomapsresulting from assay combinations containing TNF-α. This resultindicates that the test compound acts through a pathway that is distinctfrom the IL-1 and IFN-γ pathways but that cannot be distinguished fromthe TNF-α pathway in these assay combinations. To confirm that the testcompound acts through the TNF-α pathway, and to identify the pathwaystep targeted by the test agent, the test agent is evaluated in assaycombinations that contain known inhibitors of the TNF-α pathway. Therecombinant fusion protein, p55-Fc, is an example of a known inhibitorof the TNF-α pathway.

[0240] As shown in FIG. 9, confluent cultures of HUVEC cells are treatedwith Act-anti-p55 in the presence or absence of p55-Fc. After 24 hours,cultures are washed and evaluated for the cell surface expression ofICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6)and MIG (7) by cell-based ELISA performed as described in FIG. 1. FIG. 9shows the relative expression (y-axis) of each parameter α-axis) asaverage value of the OD measured at 450 nm of triplicate samples. Themean +/−SD from triplicate samples are shown. * indicates p<0.05comparing results obtained with Act-anti-p55 or Act-anti-p55+p55-Fc tothe Control.

[0241] As shown in FIG. 9, p55-Fc fusion protein, a soluble form of thep55 TNF-α receptor, that blocks TNF-α binding to the TNF-α receptor,alters the biomap generated by the test agent. This demonstrates thatthe pathway step targeted by the test agent is upstream or includes thep55 TNF-α receptor. Since a neutralizing antibody to human TNF-α doesnot alter the biomap generated by the test agent, the target pathwaystep of the test agent does not include human TNF-α.

EXAMPLE 5 DRUG INTERACTION SCREENING

[0242] The present invention is useful for analysis of combinatorialdrug interactions. Drug interactions occur if the presence of two drugsproduces a readout response pattern, or biomap, different from thoseproduced by either compound alone in an assay combination. Drugs may acton independent molecular targets within the cell but nonetheless producea combined cellular phenotype that is distinct and potentiallyphysiologically or therapeutically different in its effects. Drugcombinations may have synergistic or counteracting effects, in which onecompound enhances or suppresses the effects of another on a parameter orparameters, or alters the dose response, and may imply a more complexdrug interaction at the level of intracellular pathways. Interaction maybe beneficial if resulting combined activity is desirable;alternatively, interaction may be detrimental if the resulting combinedactivity is undesirable. The desirability of a particular druginteraction activity depends on the context. For example, a drugcombination that results in increased toxicity compared to either drugalone may be undesirable for an anti-inflammatory therapeutic, butdesirable for a cancer therapeutic. The present invention is highlyuseful for distinguishing combinatorial drug activities since the assaycombinations described are designed to measure the outcome of multiplesignaling pathways and their interactions.

[0243] A neutralizing antibody to TNF-α and a neutralizing antibody toIL-1 are both active compounds when screened in the optimized assaycombination of Example 1 (FIG. 10A). Confluent cultures of HUVEC cellsare treated with TNF-α (5 ng/ml)+IFN-γ (100 ng/ml)+IL-1 (20 ng/ml) inthe presence or absence of neutralizing antibodies to IL-1, TNF-α or thecombination. Antibody concentrations are in excess as increasedconcentrations of antibodies does not further alter the biomaps. After24 hours, cultures are washed and evaluated for the cell surfaceexpression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31(5), HLA-DR (6) and MIG (7) by cell-based ELISA performed as describedin FIG. 1. In FIG. 10A the relative expression of each parameter isshown along the y-axis as average value of the OD measured at 450 nm oftriplicate samples. The mean +/−SD from triplicate samples are shown.FIG. 10B shows a color-coded representation of the resulting biomapsprepared from the data coded as described in FIG. 2B. FIG. 10Bdemonstrates that when saturating concentrations of the neutralizingantibodies to TNF-α and IL-1 are included together in the assaycombination, a biomap is obtained that is different from the biomapobtained by assay combinations containing each test agent individually,even though the test agents are provided at saturating (excess)concentrations. Compounds that result in similar biomaps are diagnosticof inhibitors that target both the IL-1 and TNF-α pathways. The presentsystem therefore provides an assay system for screening for anddistinguishing such inhibitors.

EXAMPLE 6 DRUG INTERACTION SCREENING

[0244] The present invention is useful for the identification of druginteractions or drug combinations that are beneficial. For the presentexample, the NFκB inhibitor PPM-18 (at 2 μM) (Yu, Biochem. J. 328:363,1997) and the tyrosine kinase inhibitor AG126 (25 μM) (Novogrodsky,Science 264, 1319, 1994) are both active compounds when screened in theassay combination of Example 1 (FIG. 11A). Confluent cultures of HUVECcells are treated with TNF-α (5 ng/ml)+IFN-γ (100 ng/ml)+IL-1 (20 ng/ml)in the presence or absence of the tyrphostin AG126 (25 μM), PPM-18 (2μM) or the combination. After 24 hours, cultures are washed andevaluated for the cell surface expression of ICAM-1 (1), VCAM-1 (2),E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7) by cell-basedELISA performed as described in FIG. 1. The relative expression of eachparameter is shown in FIG. 11A as average value of the OD measured at450 nm of triplicate samples. The mean +/−SD from triplicate samples areshown. FIG. 11B shows a color-coded representation of the resultingbiomaps prepared from the data, coded as described in FIG. 2B.

[0245] In this example, higher concentrations of either drug (2-fold)when tested alone result in cellular toxicity. Together, however, thecombination of PPM-18 and AG126 at non-toxic concentrations produces acombined cellular phenotype that is additive for the effect on biomapparameters, but is not toxic to cells (FIG. 11B). The present system,therefore, provides an assay system for screening for compounds thatsynergize with inhibitors of NFκB, or with tyrosine kinase inhibitors toproduce a desirable phenotype, without resulting in cellular toxicity.

EXAMPLE 7 REGULATORS OF ENDOTHELIAL CELL RESPONSES TO ALLERGICINFLAMMATION

[0246] The present invention is applied for the screening of compoundsfor use in treating allergic inflammatory responses such as allergy,asthma, atopic dermatitis and chronic inflammatory diseases disposedtowards aTh2 phenotype or modulation of Th2 type immune responses.

[0247] Primary human umbilical vein endothelial cells (HUVEC) are used.Other cells that may replace HUVEC in the screen include primarymicrovascular endothelial cells, aortic or arteriolar endothelial cellsor endothelial cell lines such as EAhy926 or E6-E7 4-5-2G cells or humantelomerase reverse transcriptase-expressing endothelial cells (Simmons,J. Immunol., 148:267, 1992; Rhim, Carcinogenesis 19:673, 1998; Yang, J.Biol. Chem. 274:26141, 1999). 2×10⁴ cells/ml are cultured to confluencein EGM-2 (Clonetics). Other media that may replace EGM-2 include EGM(Clonetics) and Ham's F12K medium supplemented with 0.1 mg/ml heparinand 0.03-0.05 mg/ml endothelial cell growth supplement (ECGS) and 10%FBS, or medium M199 (Life Technologies, Inc.) containing 20% fetalbovine serum and 2 ng/ml basic fibroblast growth factor (Jaffe, J. Clin.Invest. 52:2745, 1973; Hoshi, PNAS 81:6413, 1984).

[0248] The following are then applied for 24 hours: IL4 (20 ng/ml), HIS(10 μM) and TNF-α (5 ng/ml). In subsequent panels one or more of IL-1 (1ng/ml), IFNγ, (100 ng/ml) IL-13 (20 ng/ml), mast cell tryptase, orfibronectin are added to the initial three factors or may replace one ofthe factors. Standard concentrations of agents are employed as describedin the literature. Based on the parameters altered by the indicatedfactors, biomaps are generated for the parameters ICAM-1, VCAM-1,E-selectin, IL-8, CD31, P-selectin and Eotaxin-3. Other markers ofinterest for adding to the biomap include: Eotaxin-1, HLA-DR, MIG, Tarc,MCP-1, and IL-8. FIG. 12 shows biomaps resulting from confluent culturesof HUVEC cells treated with IL4 (20 ng/ml), HIS (10 μM), TNF-α (5ng/ml), and/or media. After 24 hours, cultures are washed and evaluatedfor the presence of the parameters ICAM-1 (1), VCAM-1 (2), E-selectin(3), IL-8 (4), CD31 (5), P-selectin (6) and eotaxin-3 (7) by cell-basedELISA performed as described in FIG. 1. FIG. 12 shows a visualrepresentation of the resulting biomaps prepared from the data, wherethe measurement obtained for each parameter is classified according toits relative change from the value obtained in the assay combinationcontaining IL4+TNF-α+HIS, and represented by shaded squares. For eachparameter and assay combination, the square is gray if the parametermeasurement is unchanged (<20% above or below the measurement in thefirst assay combination (IL-4+TNF-α+HIS)) or p>0.05, n=3; white/grayhatched indicates that the parameter measurement is moderately increased(>20% but <50%); white indicates the parameter measurement is stronglyincreased (>50%); black/gray hatched indicates that the parametermeasurement is moderated decreased (>20% but <50%); black indicates thatthe parameter measurement is strongly decreased (>50% less than thelevel measured in the first assay combination).

[0249] A database of biomaps is generated from a panel of assaycombinations that include the presence and absence of each biologicallyactive factor; and reference drugs or agents including inhibitors ofsignaling pathways such as NFkB and STAT inhibitors, anti-histamine orhistamine receptor antagonists; as well as immune stimulatory agentsincluding pathogens or pathogen components, that are screened andbiomaps generated that show the changes in the markers with thedifferent agents. Many agents are given in The Pharmacologic Basis ofTherapeutics. The biomaps with the known agents are used to compare tocandidate agents. This allows the recognition of the pathway(s) thecandidate agent acts on, by comparing the changes in the level of thespecific markers for known drugs affecting known pathways and thechanges observed with the candidate agent. In addition to further add tothe utility of the biomap, one may include in the database referencebiomaps generated from assay panels containing cells with geneticconstructs that selectively target or modulate specific cellularpathways (e.g. NFkB, MAP kinase, etc), or cells that contain knowngenetic mutations.

EXAMPLE 8 REGULATORS OF EPITHELIAL CELL RESPONSES TO INFLAMMATION

[0250] The present invention is applied for the screening of compoundsthat regulate epithelial cell responses to inflammation.

[0251] Normal human epithelial keratinocytes (NHEK) (5×10⁴ cells/ml) arecultured to 80% confluence in serum free Keratinocyte Basal Medium-2(Clonetics CC3103) supplemented with BPE (30 μg/ml), hEGF (100 ng/ml),insulin (5 μg/ml), transferrin (10 μg/ml), and epinephrine (500 ng/ml).Other cells that may substitute for NHEK include the spontaneouslyimmortalized keratinocyte cell line, HaCaT (Boukamp, J. Cell Biol.106:761, 1988), normal human lung epithelial cells (NHLE), renal,mammary and intestinal epithelial cells. One or more of the followingare applied for 48 hours: IFN-γ (50 ng/ml), TNF-α (50 ng/ml) and IL-1(20 ng/ml). Based on the parameters altered by the indicated factors,biomaps are generated for the parameters MIG, ICAM-1, CD44, IL-8, Mip-3alpha (CCCL20), MCP-1, and E-Cadherin. Other parameters of interest forincluding in biomaps are: CD40, IP-10, EGF-Receptor, IL-6, IL-15Ralpha,CD1d, CD80, CD86, TARC, eotaxin-1, eotaxin-3, HLA-DR and CD95. Otherfactors of interest for including in assay combinations include TGFβ,IL-9, GM-CSF, CD40L and IL-17 activities.

[0252] In FIG. 13, confluent cultures of NHEK cells are treated with oneor more of IFN-γ (50 ng/ml), TNF-α (50 ng/ml), IL-1 (20 ng/ml) and/orbase media. After 48 hours, cultures are washed and evaluated for thepresence of the parameters Mig (1), ICAM-1 (2), CD44 (3), IL-8 (4),Mip-3 alpha (5), MCP-1 (6), and E-Cadherin (7) by cell-based ELISAperformed as described in FIG. 1. FIG. 13 shows a visual representationof the resulting biomaps prepared from the data, where the measurementobtained for each parameter is classified according to its relativechange from the value obtained in the assay combination containingIL-1+IFNγ, and represented by shaded squares. For each parameter andassay combination, the square is gray if the parameter measurement isunchanged (<20% above or below the measurement in the first assaycombination (IL-1+IFN-γ)) or p>0.05, n=3; white/gray hatched indicatesthat the parameter measurement is moderately increased (>20% but <50%);white indicates the parameter measurement is strongly increased (>50%);black/gray hatched indicates that the parameter measurement is moderateddecreased (>20% but <50%); black indicates that the parametermeasurement is strongly decreased (>50% less than the level measured inthe first assay combination).

[0253] A database of biomaps is generated from a panel of assaycombinations that include the presence and absence of each biologicallyactive factor; and reference drugs or agents including inhibitors ofsignaling pathways such as NFkB and STATs, as well as immune stimulatoryagents including pathogens or pathogen components, that are screened andbiomaps generated that show the changes in the markers with thedifferent agents. Many agents are given in The Pharmacologic Basis ofTherapeutics. The biomaps with the known agents are used to compare tocandidate agents. This allows the recognition of the pathway(s) thecandidate agent acts on, by comparing the changes in the level of thespecific markers for known drugs affecting known pathways and thechanges observed with the candidate agent. In addition to further add tothe utility of the biomap, one may include in the database referencebiomaps generated from assay panels containing cells with geneticconstructs that selectively target or modulate specific cellularpathways (e.g. NFkB, MAP kinase, etc), or cells that contain knowngenetic mutations.

EXAMPLE 9 REGULATORS OF T CELL RESPONSES—T CELL-ENDOTHELIAL CELLCO-CULTURES

[0254] The present invention is applied for the screening of compoundsfor altering immune and/or inflammatory conditions that involve T cells.

[0255] Primary human umbilical vein endothelial cells and the human Tcell line, KIT255 are used. Other cells that may replace HUVEC in thescreen include primary microvascular endothelial cells or aorticendothelial cells. 2×10⁴ HUVEC/ml were cultured to confluence in EGM-2(Clonetics). Other media that may replace EGM-2 include EGM (Clonetics)and Ham's F12K medium supplemented with 0.1 mg/ml heparin and 0.03-0.05mg/ml endothelial cell growth supplement (ECGS) and 10% FBS, or mediumM199 (Life Technologies, Inc.) containing 20% fetal bovine serum and 2ng/ml basic fibroblast growth factor (Jaffe, J. Clin. Invest. 52:2745,1973; Hoshi, PNAS 81:6413, 1984). One or more of the following are thenapplied: 10³ KIT255 cells, IL-2 (10 ng/ml), IL-12 (10 ng/ml), and orbase media. After 24 hours, cultures are washed and evaluated for thepresence of the parameters ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8(4), CD31 (5), HLA-DR (6) and MIG (7) by cell based ELISA as describedin FIG. 1 and shown in FIG. 14. In this figure, analysis performed bycell based ELISA provides readout patterns that combine HUVEC and T cellreadouts. FIG. 14 demonstrates that the biomaps derived from assaycombinations containing KIT255 cells +/−IL-2 and IL-12 can bedistinguished. Other cells that may replace KIT255 include humanperipheral blood leukocytes, human peripheral blood T cells, humanperipheral blood CD3+ cells, and the human T cell lines Jurkat andHUT78. In subsequent panels, one or more of: PHA, IL-6, IL-7, activatingantibody to CD3, activating antibody to CD28, IL-1, TNF-α, IFN-γ, IL-4,IL-13 or neutralizing antibodies to IL-1, IL-2, TNF-α, IFN-γ, IL-12and/or IL-4 are applied. Other markers of interest for adding to thebiomap include MCP-1, IP-10, cutaneous lymphocyte antigen (CLA), CXCR3,CCR3, TNF-α, IFN-γ, IL-2, IL-4, alpha4beta7, alphaEbeta7, andL-selectin. Analytical methods that distinguish T cells from endothelialcells, such as flow cytometry or image analytical techniques can beemployed. A database of biomaps is generated from a panel of assaycombinations that include anti-inflammatory drug compounds includinginhibitors of T cell activation and/or T cell proliferation, calcineurininhibitors, etc. are screened and biomaps are generated that reflect thechanges in the markers with the different agents. Such agents are givenin The Pharmacologic Basis of Therapeutics. The biomaps with the knownagents are used to compare to candidate immunomodulatory agents. Thisallows the recognition of the pathway(s) the candidate test agent actson, by comparing the changes in the level of the specific markers forknown agents affecting known pathways and the changes observed with thecandidate test agent. In addition to further add to the utility of thebiomap, one may include in the database reference biomaps generated fromassay panels containing cells with genetic constructs that selectivelytarget or modulate specific cellular pathways (e.g. NFAT, calcineurin,NFκB, MAP kinase, etc), or cells that contain known genetic mutations,e.g. Jurkat cell lines that lack lck, CD45, etc. (Yamasaki, J. Biol.Chem. 272:14787, 1997).

EXAMPLE 10 FUNCTION OF GENES IN CELLULAR RESPONSES IN INFLAMMATION

[0256] The present invention is useful for identifying functions ofgenes and their expressed gene products. For example, genes whoseproducts regulate inflammation can be identified in an inflammationmodel using human endothelial cells as an indicator cell type. A panelof assay combinations that reproduce aspects of the response of theendothelial cells to different types of inflammatory processes is used,as described in Example 1.

[0257] Primary human umbilical vein endothelial cells (HUVEC) are used.Other cells that may replace HUVEC in the screen include primarymicrovascular endothelial cells, aortic or arteriolar endothelial cellsor endothelial cell lines such as EAhy926 or E6-E7 4-5-2G cells or humantelomerase reverse transcriptase-expressing endothelial cells (Simmons,J. Immunol., 148:267, 1992; Rhim, Carcinogenesis 19:673, 1998; Yang, J.Biol. Chem. 274:26141, 1999). Endothelial cells in exponential growthphase are transduced with retroviral vectors or tranfected with plasmidvectors encoding test genes. A marker gene is incorporated in the vectorthat allows monitoring of expression. A suitable retroviral vector isdescribed in FIG. 15, and is derived from the MoMLV-based pFB vector(Stratagene). Other standard methods for transduction or transfection ofcells for expression of genes can be substituted.

[0258] Test genes are inserted downstream of the MoMLV LTR. The markergene is the truncated form of the human nerve growth factor receptor(NGFR)) (Mavilio, Blood 83:1988, 1994) separated from the test gene byan independent ribosomal entry site sequence (IRES). The IRES is 100 bpfragment from human elF4G IRES sequence (Gan, J. Biol. Chem. 273:5006,1988). In the example shown in FIG. 16, the test gene used is human Ikappa B-related Bcl-3 (Dechend, Oncogene, 18:3316, 1999). Retroviralvector plasmid DNA is transfected into AmphoPack-293 cells (Clonetech)by modified calcium phosphate method according to manufacturer'sprotocol (MBS transfection kit, Stratagene). Cell supernatants areharvested 48 hours post-transfection, filtered to remove cell debris(0.45 μm) and transferred onto exponentially growing HUVEC cells. DEAEdextran (conc 10 μg/ml) is added to facilitate vector transduction.After 5-8 hour incubation the viral supernatant is removed and cellscultured for an additional 40 hours. Gene transfer efficiency isdetermined by FACS using NGFR-specific monoclonal antibodies, and in theexperiment shown, is >90%. Transduced cells are re-plated into 96-wellplates, and cultured to confluence for biomap analysis.

[0259] Confluent transduced or control HUVEC cells are treated with thecombination of TNF-α (5 ng/ml)+IFN-γ (100 ng/ml)+IL-1 (1 ng/ml); or withTNF-α (5 ng/ml), IL-1 (1 ng/ml) or media only. After 24 hours, culturesare washed and evaluated for the cell surface expression of ICAM-1 (1),VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7)as under Example 1. FIG. 16 shows how over-expression of Bcl-3 resultsin altered biomaps in the assay panel used. Expression of Bcl-3 resultsin increased expression of ICAM-1 in endothelial cells under basalconditions, and enhanced expression of ICAM-1 and VCAM-1 in cellscultured with IL-1. It does not alter the biomaps resulting from assaycombinations containing TNFα or TNF-α+IFN-γ+IL-1. FIG. 16 shows a visualrepresentation of the biomaps derived from the resulting data. Thusexpression of Bcl-3 yields a distinctive biomap in the assay panelemployed. It can be concluded from this biomap panel that bcl-3 altersthe basal reference bioamp and the biomap from IL1, but not that fromTNF. The results define bcl-3 as a potential target for modulation ofthe inflammatory response.

[0260] This example demonstrates that the biomap analysis is useful foridentifying gene function. In this particular case the biomap analysisshows that Bcl-3 is involved in regulating expression of ICAM-1 andVCAM-1, and thus inflammatory states. Furthermore biomap analysisidentifies cellular states in which gene functions alter cellularresponses (e.g. IL-1 versus TNF biomap). Information about the functionof unknown genes is obtained by comparing biomaps of unknown genes tothe distinctive biomaps determined by the known gene products, drugs,antibodies, and other agents in various cellular states.

EXAMPLE 11 DISCRIMINATION OF PATHWAYS: REGULATION OF APOPTOSIS

[0261] The present invention is useful for discriminating biologicallyactive agents and genes that act on different pathways. Pthways involvedin cellular apoptosis can be distinguished from those involved inregulation of adhesion molecules and cytokines in inflammation, andagents that modify these pathways can be identified.

[0262] A panel of assay combinations that reproduces aspects of theresponse of the endothelial cells to inflammatory processes and stimulienhancing apoptosis is used. TNFα and ceramide are factors known toenhance cell apoptosis in endothelial cells (Slowik, Lab Invest. 77:257,1997). Endothelial cells cultured under basal conditions display a lowlevel of cell damage as measured by release of cytoplasmic lactatedehydrogenase from cells into the supernatant. This level is enhanced incultures comprising TNF-α, ceramide, or the combination of ceramide andTNF-α.

[0263] Retroviral vectors (FIG. 15) derived from the MSCV-based pMSCVneovector (Clontech) are used to express genes in the cultured endothelialcells. Other standard vectors or tranfection protocols can besubstituted. Test genes are inserted downstream of the MSCV LTR, themarker gene is the enhanced green fluorescent protein (GFP) and the IRESis 600 bp fragment from EMCV virus (Jang, J. Virol. 63:1651, 1989). Inthe example in FIG. 17, test genes are human Bcl-2 and Bcl-xL.Retroviral vector plasmid DNA is transfected into AmphoPack-293 cells(Clontech) by modified calcium phosphate method according tomanufacturer's protocol (MBS transfection kit, Stratagene). Cellsupernatants are harvested 48 hours post-transfection, filtered toremove cell debris (0.45 μm) and transferred onto exponentially growingHUVEC cells. DEAE dextran (conc 10 μg/ml) is added to facilitate vectortransduction. After a 5-8 hour incubation period viral supernatants areremoved and cells cultured for an additional 40 hours. Gene transferefficiency is determined by FACS, and is typically ≧80 percent.Transduced cells are re-plated into 96-well plates for biomap analysis.Confluent HUVEC cells are treated with either ceramide (10 μm), TNF-α (5ng/ml), ceramide (10 μm)+TNF-α (5 ng/ml), or TNF-α (5 ng/ml)+IFN-g (100ng/ml)+IL-1 (1 ng/ml), or media only. After 24 hours, transduced cellsare evaluated for the surface expression ICAM-1 (1), VCAM-1 (2), and MIG(3) by cell-based ELISA for biomap analysis. For the expanded biomap,cell supernatants at 24 hours are collected and analyzed for thepresence of LDH (4). In the present example, over-expression of Bcl-2and Bcl-xL results in altered biomap parameters that reflect an effecton the apoptotic pathway (e.g. FIG. 17, parameter 4, LDH), but notbiomap parameters that reflect adhesion and cytokine regulation pathways(parameters 1, 2 and 3; ICAM-1, VCAM-1 and MIG, respectively).

[0264] This example clearly shows the utility of biomap analysis fordistinguishing gene effects on multiple cell functions and pathways, andin the present example, for identifying genes modulating apoptosispathways.

EXAMPLE 12 FUNCTION OF GENES IN CELLULAR RESPONSES IN INFLAMMATION:ANTISENSE APPROACH

[0265] The present invention is useful for identifying functions ofgenes and their expressed gene products using antisense approaches. Forexample, genes whose products regulate inflammation can be identified inan inflammation model using human endothelial cells as an indicator celltype. A panel of assay combinations that reproduce aspects of theresponse of the endothelial cells to different types of inflammatoryprocesses is used, as described in Example 1.

[0266] Primary human umbilical vein endothelial cells (HUVEC) are used.Other cells that may replace HUVEC in the screen include primarymicrovascular endothelial cells, aortic or arteriolar endothelial cellsor endothelial cell lines such as EAhy926 or E6-E7 4-5-2G cells or humantelomerase reverse transcriptase-expressing endothelial cells (Simmons,J. Immunol., 148:267, 1992; Rhim, Carcinogenesis 19:673, 1998; Yang, J.Biol. Chem. 274:26141, 1999).

[0267] Morpholino phosphorodiamidate (MF) antisense oligonucleotides areused. Other chemical classes of antisense oligonucleotides that can besubstituted for morpholinos include but are not limited tophosphorotioate oligonucleotides, N3′-P5′ phosphoramidateoligonucleotides (NP), locked nucleic acid (LNA), 2′-O-methoxyethylnucleic acid (MOE), 2′-fluoro-arabinonucleic acid (FANA), peptidenucleic acids (PNA) (reviewed in Toulme, Nature Biotech. 19:17, 2001).In the example in FIG. 18, antisense oligonucleotides for TNF-R1 (p55)(5′-AGGTCAGGCACGGTGGAGAGGC-3′)(SEQ ID NO:1), and the beta-globin controloligo (5′-CCTCTTACCTCAGTTACAATTTATA-3′)(SEQ ID NO:2) (Gene Tools Inc.)are used. The transfection mixture is prepared by mixing 5 ml of stockmorpholino (0.5 mM), 500 ml water, and 4 ml of 200 mM EPEI (EthoxylatedPolyEthylenimine), vortexed, incubated at room temperature for 20minutes, and then mixed with 3.5 ml of serum-free media to give a final0.6 μM morpholino concentration. HUVEC cells are plated the day beforein 24-well plates at 4-6×10e4 cells/well. Cells are washed once withserum-free media and incubated with 0.4 ml of the morpholinotransfection mixture at 37° C. for 3 hours. Morpholino is removed,regular media (Epithelial Growth Media with 2% fetal calf serum,Clonetics) is added and cells allowed to recover overnight. Theefficiency of loading of cells with morphino is monitored in cellsincubated with a fluorescent morpholino, and is typically essentially100 percent. HUVEC cells are then treated with either TNF-α (0.5 ng/ml),or IL-1 (1 ng/ml), or media only. After 4 hours, cells are harvested andevaluated for the cell surface expression of ICAM-1 (1), VCAM-1 (2),E-selectin (3), and CD31 (4) by flow cytometry. FIG. 18 shows thatTNF-R1 antisense gives an altered biomap that is distinct from thecontrol oligo biomap (with control morpholino) upon treatment withTNF-α, but not upon treatment with IL-1. The TNF-R1 antisensespecifically blocks induction of ICAM-1 and VCAM-1 by TNF-α, while ithas no effect on induction of the same markers by the independent cellsurface receptor for IL-1.

[0268] The results illustrate the utility of the invention inidentifying the function of genes in different assay combinations in anassay panel. This example clearly shows the utility of biomap analysisfor distinguishing gene effects on multiple cell functions and pathways,and in the present example, for identifying genes involved in signalingby a proinflammatory cytokine.

EXAMPLE 13 CANCER APPLICATIONS—COLON CARCINOMA

[0269] The present invention is applied for the screening of compoundsfor use in treating colon carcinoma.

[0270] The human colon carcinoma cell line HT-29 is used. Other coloncarcinoma cells lines that may replace HT-29 in the screen includeCaCo-2, Colo201, DLD-1, HCC 2998, HCT116, KM-12, LoVo, LS-174, SW-48,SW-480, SW-620, SW-83 or T-84; or primary tumor cells. 2×10⁴ cells/mlare cultured in McCoy's 5a Medium containing 1.5 mM L-glutamine and 10%FBS. Other media that may replace McCoy's 5a Medium include Eagle'sMedium Ham's F12 Medium, Dulbecco's Modified Eagle's Medium andchemically defined McCoy's 5A serum-free medium (Life Technologies,Inc.) supplemented with 20 μg/ml insulin, 4 μg/ml transferrin, and 10ng/ml epidermal growth factor. Other conditions of interest that may beused in subsequent assay combinations include assaying cultures withduring log phase growth. Following overnight serum starvation thefollowing are then applied for 48 hours: IGF-II (10 nM), TGF-β (10ng/ml), and TNF-α (100 ng/ml). In subsequent panels one or more of IL-1(10 ng/ml), IL-4 (20 ng/ml), IL-13 (30 ng/ml), TGF-β (10 ng/ml), IFN-γ(200 U/ml), epidermal growth factor (10 ng/ml) and IL-6; and/orneutralizing antibodies to autocrine factors, IGF-II, IL-8 or TGF-β orthe receptor IGF-R I, are added to the initial three factors or mayreplace one of the three factors. Standard concentrations of agents areemployed as described in the literature (Freier, Gut 44:704, 1999;Naylor, Cancer Res. 50:4436, 1990; Kanai, Br. J. Cancer 82:1717, 2000;Wright, JBC 274:17193, 1999; Zarrilli, JBC 271:8108, 1996; Murata, JBC270:30829, 1996; Cardillo, J. Exp. Clin. Cancer Res. 16:281, 997;Rajagopal, Int. J. Cancer 62:661, 1995; Barth, Cancer 78:1168, 1996).Based on the parameters altered by the indicated factors, biomaps aregenerated for the parameters integrin α_(v), ICAM-1, CD44,carcinoembryonic antigen (CEA) and α₅β₁. Other markers of interest foradding to the biomap include EGF-R, HLA-Class I, HLA-DR,poly-Ig-receptor, IL-8, CA-19-9, E-cadherin, CD95, α₂α₁, α₃β₁, α₆β₁,α₆β₄, α_(v), laminin 5, urokinase-type plasminogen activator receptor(uPAR), MIP-3α and TNFR-1 (Kelly, Am. J. Physiol. 263, G864-70, 1992;Moller, Int. J. Cancer, 57:371, 1994). Parameters of interest alsoinclude parameters indicative of cell damage and apoptosis includingreleased cytoplasmic lactate dehydrogenase (LDH) or mitochondrialcytochrome c, appearance of APO2.7 epitope or active caspase-3 (Zhang,J. Immunol., 157:3980, 1996; Bussing, Cytometry 37:133, 1999).Parameters indicative of cell proliferation are also of interest andinclude Ki-67 and PCNA (Landberg, Cytometry, 13:230, 1992).

[0271] A database of biomaps is generated from a panel of assaycombinations that include the differentiation-inducing agent butyrate,and known anti-cancer agents. DNA synthesis inhibitors, nucleosideanalogs, topoisomerase inhibitors, and microtubule function inhibitorsare screened and a biomap generated that shows the changes in themarkers with the different anti-cancer agents. Such compounds are givenin Weinstein, 1997, and The Pharmacologic Basis of Therapeutics. Thebiomaps with the known agents are used to compare to candidateanti-cancer drugs. This allows the recognition of the pathway(s) thecandidate anticancer drug acts on, by comparing the changes in the levelof the specific markers for known drugs affecting known pathways and thechanges observed with the candidate drug. In addition, to further add tothe utility of the biomap, one may include in the database referencebiomaps generated from assay panels containing cells with geneticconstructs that selectively target or modulate specific cellularpathways (e.g. ras, p53, NFκB, MAP kinase, etc), or cells that containknown genetic mutations (e.g. HT-29 cells contain a p53 mutation, etc.).

EXAMPLE 14 CANCER APPLICATIONS—PROSTATE CANCER

[0272] The present invention is applied for the screening of compoundsfor use in treating prostate cancer.

[0273] The human prostate carcinoma cell line LNCaP is used. Otherprostate carcinoma cells lines that may replace LNCaP in the screeninclude DU-145, PPC-1, PC-3, MDA PCA 2b, JCA-1; normal prostateepithelial cells or primary tumor cells. 2×10⁴ cells/ml are cultured inDulbecco's Modified Eagle's Medium (DMEM) containing 10% FBS. Othermedia that may replace Dulbecco's Modified Eagle's Medium include RPMI,HAMS F12, DMEM containing charcoal-stripped serum or serum-free DMEMsupplemented with 0.5% BSA. Other conditions of interest that may beused in subsequent assay combinations include assaying cultures withduring log phase growth. Following overnight serum starvation thefollowing are then applied for 24 hours: 5-dihydrotestosterone (10 nM),TNF-α (200 U/ml) and IL-6 (50 ng/ml). In subsequent panels one or moreof IL-1 (10 ng/ml), IFN-γ (500 U/ml), TGF-α (10 ng/ml), epidermal growthfactor (10 ng/ml) and IGF-II (10 nM); and/or neutralizing antibodies toautocrine factors, IGF-II, EGF, IL-6 or TGF-β or their receptors; and/orhypoxic conditions are added to the initial three factors or may replaceone of the three factors. Standard concentrations of agents are employedas described in the literature (Sokoloff, Cancer 77:1862, 1996; Qiu,PNAS 95:3644, 1998; Hsiao, JBC 274:22373, 1999). Based on the parametersaltered by the indicated factors, biomaps are generated for theparameters prostate specific antigen (PSA), E-cadherin, IL-8, epidermalgrowth factor receptor and vascular endothelial growth factor (VEGF).Other markers of interest for adding to the biomap include epidermalgrowth factor receptor, Her-2/neu EGF-R, HLA-class I, HLA-DR, CD95, α3,α₂β₁, α₅β₁, α_(v)β₃, ICAM-1, MIP-3α and CD44. Parameters of interestalso include parameters indicative of cell damage and apoptosisincluding released cytoplasmic lactate dehydrogenase (LDH) ormitochondrial cytochrome c, appearance of APO2.7 epitope or activecaspase-3 (Zhang, J. Immunol., 157:3980, 1996; Bussing, Cytometry37:133, 1999). Parameters indicative of cell proliferation are also ofinterest and include Ki-67 and PCNA (Landberg, Cytometry, 13:230, 1992).

[0274] A database of biomaps is generated from a panel of assaycombinations that include the differentiation-inducing agents butyrate,calcitriol, and known anti-cancer agents that include anti-androgens,DNA synthesis inhibitors, nucleoside analogs, topoisomerase inhibitors,and microtubule function inhibitors. These factors are screened and abiomap generated that shows the changes in the markers with thedifferent anti-cancer agents. Such compounds are given in Weinstein,1997, and The Pharmacologic Basis of Therapeutics. The biomaps with theknown agents are used to compare to candidate anti-cancer drugs. Thisallows the recognition of the pathway(s) the candidate anticancer drugacts on, by comparing the changes in the level of the specific markersfor known drugs affecting known pathways and the changes observed withthe candidate drug. In addition to further add to the utility of thebiomap, one may include in the database reference biomaps generated fromassay panels containing cells with genetic constructs that selectivelytarget or modulate specific cellular pathways (e.g. ras, p53, NFκB, MAPkinase, etc), or cells that contain known genetic mutations (e.g. LNCaPcells contain a K-ras mutation, etc.).

EXAMPLE 15 CANCER APPLICATIONS—BREAST CANCER

[0275] The present invention is applied for the screening of compoundsfor use in treating breast cancer.

[0276] The human breast cell line MCF-7 is used. Other breast cancercell lines that may replace MCF-2 in the screen include AU-565, HCC38,MCF-7, MDA-MB-231, MIB 157, SW-527, T47D, UACC-812, UACC- or ZR-75-1;primary mammary epithelial cells or primary tumor cells. 2×10⁴ cells/mlare cultured in RPMI medium 10% FBS. Other media that may replace RPMIinclude Dulbecco's Modified Eagle's Medium containing 20% FBS. Otherconditions of interest that may be used in subsequent assay combinationsinclude assaying cultures with during log phase growth. Followingovernight serum starvation the following are then applied for 24 hours:estrogen (10-7 M), IL-4 (50 ng/ml), antibody to Her-2/neu, IL-1β (10ng/ml). In subsequent panels one or more of IGF-I (5 nM), TNF-α (100ng/ml), IFN-γ (200 U/ml), IL-13 (30 ng/ml), TGF-β (10 ng/ml), epidermalgrowth factor (10 ng/ml) and IL-6; and/or neutralizing antibodies toautocrine factors, IL-1, TGF-β or the receptor IGF-R I, are added to theinitial three factors or may replace one of the three factors. Standardconcentrations of agents are employed as described in the literature(Jackson, JBC 273:9994, 1998; He, PNAS 97:5768, 2000). Based on theparameters altered by the indicated factors, biomaps are generated forthe parameters ICAM-1 (CD54), IL-8, MCP-1, E-cadherin, HLA-DR, CD44,carcinoembryonic antigen (CEA, CD66e), MIP-3α and α₅β₁. Other markers ofinterest for adding to the biomap include EGF-R, HLA-1,poly-Ig-receptor, IL-8, CA-19-9, CD95, α₂β₁, α₃β₁, α₆, α₆β₄, α_(v),laminin 5, urokinase-type plasminogen activator receptor (uPAR), andTNFR-I. Parameters of interest also include parameters indicative ofcell damage and apoptosis including released cytoplasmic lactatedehydrogenase (LDH) or mitochondrial cytochrome c, appearance of APO2.7epitope or active caspase-3 (Koester, Cytometry, 33:324, 1998; Zhang, J.Immunol., 157:3980, 1996; Bussing, Cytometry 37:133, 1999). Parametersindicative of cell proliferation are also of interest and include Ki-67and PCNA (Landberg, Cytometry, 13:230, 1992).

[0277] A database of biomaps is generated from a panel of assaycombinations that include the differentiation-inducing agent calcitriol,and known anti-cancer agents. anti-estrogens, DNA synthesis inhibitors,nucleoside analogs, topoisomerase inhibitors, and microtubule functioninhibitors are screened and a biomap generated that shows the changes inthe markers with the different anti-cancer agents. Such compounds aregiven in Weinstein, 1997, and The Pharmacologic Basis of Therapeutics.The biomaps with the known agents are used to compare to candidateanti-cancer drugs. This allows the recognition of the pathway(s) thecandidate anticancer drug acts on, by comparing the changes in the levelof the specific markers for known drugs affecting known pathways and thechanges observed with the candidate drug. In addition to further add tothe utility of the biomap, one may include in the database referencebiomaps generated from assay panels containing cells with geneticconstructs that selectively target or modulate specific cellularpathways (e.g. ras, p53, NFκB, MAP kinase, etc), or cells that containknown genetic mutations (e.g. MDA-MB-231 cells contain a mutant p53,etc.).

EXAMPLE 16 ANGIOGENESIS INHIBITORS

[0278] The present invention is applied for the screening of compoundsthat inhibit or modulate angiogenesis for treatment of vascularizedneoplasms, rheumatoid arthritis and other disorders, or for conditionswhere vascular remodeling is beneficial.

[0279] Primary human umbilical vein endothelial cells are used. Othercells that may replace HUVEC in the screen include primary microvascularendothelial cells, aortic endothelial cells. 2×10⁴ cells/ml are culturedto confluence in EGM-2 (Clonetics). Other media that may replace EGM-2include EGM (Clonetics) and Ham's F12K medium supplemented with 0.1mg/ml heparin and 0.03-0.05 mg/ml endothelial cell growth supplement(ECGS) and 10% FBS, or medium M199 (Life Technologies, Inc.) containing20% fetal bovine serum and 2 ng/ml basic fibroblast growth factor(Jaffe, J. Clin. Invest. 52:2745, 1973; Hoshi, PNAS 81:6413, 1984).Following overnight serum starvation, the following are then applied for24 hours: VEGF (10 ng/ml), TNF-α (1 ng/ml) and bFGF (10 ng/ml). Insubsequent panels one or more of IL-4 (20 ng/ml), IL-13 (20 ng/ml), EGF(10 ng/ml), hydrocortisone (2 ng/ml), thrombin (0.1 U/ml), hypoxicconditions (Xu, JBC 275:24583, 2000); and/or neutralizing antibodies toautocrine factors, such as TGF-β, IL-8 or IL-6 are added to the initialthree factors or may replace one of the three factors. Standardconcentrations of agents are employed as described in the literature(Thakker, JBC 274:10002, 1999; Kikuchi, NRMGK 23:12, 2000; Woltmann,Blood 95:3146, 2000; Wu, JBC 275:5096, 2000). Based on the parametersaltered by the indicated factors, biomaps are generated for theparameters alphavbeta3, IL-8, VCAM-1, von Willebrand factor, E-selectin,fibronectin and uPAR (Friedlander, Science 270:1500, 1995; Zanetta, Int.J. Cancer 85, 281, 2000). Other markers of interest for adding to thebiomap include: thrombomodulin, Tissue Factor, MMP-2, MMP-3, α₅β₁,α_(v)β₅, CD105, CXCR4 and CD31 (St. Croix, Science 289:1197, 2000;Friedlander, Science 270:1500, 1995; Bodey, Anticancer Res. 18:3621,1998).

[0280] A database of biomaps is generated from a panel of assaycombinations that include the known angiogenesis inhibitors and agentsare screened and a biomap generated that shows the changes in themarkers with the different anti-angiogenesis agents. Suchanti-angiogenic compounds include growth factor signaling inhibitors andare given in The Pharmacologic Basis of Therapeutics. The biomaps withthe known agents are used to compare to candidate anti-angiogenic drugs.This allows the recognition of the pathway(s) the candidateanti-angiogenic drug acts on, by comparing the changes in the level ofthe specific markers for known drugs affecting known pathways and thechanges observed with the candidate drug. In addition, to further add tothe utility of the biomap, one may include in the database referencebiomaps generated from assay panels containing cells with geneticconstructs that selectively target or modulate specific cellularpathways (e.g. ras, rho, NFκB, MAP kinase, etc), (e.g. HUVECretrovirally transformed to overexpress bcl-2 (Zheng, J. Immunol164:4665, 1999) or cells that contain known genetic mutations.

EXAMPLE 17 CARDIOVASCULAR DISEASE

[0281] The present invention is applied for the screening of compoundsfor use in treating vascular dysfunction associated with cardiovasculardisease, hypertension, diabetes and autoimmune disease.

[0282] Human aortic endothelial cells are used. Other cells that mayreplace human aortic endothelial cells include: human umbilical veinendothelial cells and human microvascular endothelial cells. 2×10⁴cells/ml are cultured to confluence in Endothelial cell growth medium-2(EGM-2, Clonetics Corp.) containing Epidermal Growth Factor (100 ng/ml),hydrocortisone (1 ug/ml), Vascular Endothelial Growth Factor (10 ng/ml),Fibroblast Growth Factor B (30 ng/ml), Insulin Like Growth Factor-1 (10nM) and 2% FBS. Other media that may replace EGM-2 include Medium 199containing ECGF (50 ug/ml) and heparin (100 ug/ml); Medium 199supplemented with 10% FBS; or endothelial cell basal medium (CloneticsCorp.) containing 1% bovine serum albumin (Thornton, Science 222:623,1983; Jaffe, J. Clin. Invest, 52:2745, 1974; Wu, J. Biol. Chem.275:5096, 2000). The following are then applied for 24 hours:angiotensin-II (100 nM), TNF-α (5 ng/ml) and thrombin (10 U/ml) (Dietz,Basic Res. Cardiology 93 Suppl2:101, 1998; Lommi, Eur. Heart. J.18:1620, 1997; Jafri, Semin. Thromb. Hemost. 23:543, 1997). Insubsequent panels one or more of IL-1 (10 ng/ml), IFN-γ (100 ng/ml) IL-4(20 ng/ml), IL-13 (30 ng/ml), TGF-beta (10 ng/ml), endothelin-1 (100nM), aldosterone (1 uM), oxidized LDL (100 ug/ml), or minimally modifiedLDL are added to the initial three factors or may replace one of thethree factors (Brown, J Clin Endocrinol Metab, 85:336, 2000; de Boer, J.Pathol. 188:174, 1999; Berliner, J. Clin. Invest. 85:1260, 1990).Standard concentrations of agents are employed as described in theliterature (Kaplanski, J. Immunol 158:5435, 1997; Hofman, Blood 92:3064,1998; Li, Circulation 102:1970, 2000; Essler, JBC 274:30361, 1999;Brown, J Clin Endocrinol Metab, 85:336, 2000). Based on the parametersaltered by the indicated factors, biomaps are generated for theparameters ICAM-1, vWF, E-selectin, P-selectin, IL-8, PAI-1, angiotensinconverting enzyme (ACE, CD143), platelet-derived growth factor (PDGF)and MCP-1 (Devaux, Eur. Heart J. 18:470, 1997; Kessler, Diabetes Metab.24:327, 1998; Becker, Z. Kardiol. 89:160, 2000; Kaplanski, J. Immunol.158:5435, 1997; Li, Circulation 102:1970, 2000). Other markers ofinterest for adding to the biomap include, angiotensin-1 receptor,urokinase-type plasminogen activator receptor (uPAR, CD87), endothelin-1receptor, tissue factor (CD142), fibrinogen-binding activity, MIGchemokine, and CD36 (Paramo, Br. Med. J. 291:573, 1985; Fukuhara,Hypertension 35:353, 2000; Noda-Heiny, Arterioscler Thromb Vasc. Biol.15:37, 1995; de Prost, J. Cardiovasc. Pharmacol., 25 Suppl2:S114, 1995;van de Stolpe, Thromb Haemost 75:182, 1996; Mach, J. Clin. Invest.,104:1041, 1999; Nicholson, Ann. N.Y. Acad. Sci., 902:128, 2000). Adatabase of biomaps is generated from a panel of assay combinations thatinclude known cardioprotective agents including beta blockers and otherhypertensive drugs, ACE inhibitors, AT1 antagonists, andanti-aldosterones; statins; and others, are screened and a biomapgenerated that shows the changes in the markers with the differentanti-cancer agents. Such compounds are given in The Pharmacologic Basisof Therapeutics. The biomaps with the known agents are used to compareto candidate cardioprotective drugs. This allows the recognition of thepathway(s) the candidate drug acts on, by comparing the changes in thelevel of the specific markers for known drugs affecting known pathwaysand the changes observed with the candidate drug. In addition to furtheradd to the utility of the biomap, one may include in the databasereference biomaps generated from assay panels containing cells withgenetic constructs that selectively target or modulate specific cellularpathways (e.g. NFκB, MAP kinase, etc), or cells that contain knowngenetic mutations (e.g. CD36-deficiency, Yanai, Am. J. Med. Genet.93:299, 2000, etc.).

EXAMPLE 18 REGULATORS OF T CELL FUNCTION—NAIVE T CELL RESPONSES

[0283] The present invention is useful for identifying regulators of Tcell mediated inflammation and immunity. A set of assay combinationsthat reproduces aspects of the response of the naive T cells are used.

[0284] The immune cell stimulatory environment in vivo during pathogenicimmunity is characterized by the presence of multiple biologicallyactive agents including IL-1, IL-2, TNF-α, and IFN-γ, IL4, IL12, IL10,TGF beta, IL6, IL7 and IL15 and others (Picker, J. Immunol. 150:1122,1993; Picker J. Immunol:150:1105, 1993; W. Paul, Fundamental Immunology,4th Ed, 1998. Lippincott Williams & Wilkins Publishers). Optimized assaycombinations for naive T cell responses will contain at least two, andpreferably three, four or more of these biologically active agents inaddition with a primary stimulus through the T cell receptor andsecondary stimuli through co-stimulatory receptors. Concentrations ofagents are standard according to the literature. Concentrations may alsobe determined experimentally as the amount required to saturate therelevant receptor.

[0285] Primary human cord blood mononuclear cells are used. Other cellsthat may replace these cells include isolated populations of naive CD4+and/or CD8+ T cells isolated from adult human peripheral blood T cells.Cord blood mononuclear cells are isolated from blood by Ficoll-hypaquedensity gradient centrifugation as described (Ponath, JEM 183:2437,1996). Cells are then cultured at 106 cells/ml in RPMI containing 10%FBS and Staphylococcal Enterotoxin B (SEB) (1 ug/ml), anti-CD28 (10ug/ml), and IL-12 (5 ng/ml). In subsequent panels one or moreStaphylococcal Enterotoxin E (SEE), or toxic shock syndrome toxin(TSST), or antibody to CD3 (1 ug/ml) can replace or be included with SEBto provide T cell receptor stimulation. TCR stimulation throughconventional antigens or alloantigen, as in the mixed lymphocyteculture. In subsequent panels one or more of IL-1 (10 ng/ml), IL-2 (1ng/ml), IL-10, IL4 (20 ng/ml), IL-13 (30 ng/ml), TGF-b (10 ng/ml),anti-CD49d, IL-6, IL-7, IL-15, IL-18; and/or neutralizing antibodies toautocrine factors, IL-2, TNF-α, are added to the initial three factorsor may replace the IL-12. Antibodies or ligands for CD49d and CD28provide costimulatory signals. Other Alternative costimulatory signalsof interest that may be substituted for anti-CD28 and anti-CD49d includeantibodies or ligands to CD5, anti-ICOS, or anti-4-1BB. The TCR stimulusand biologically active factors are then applied for 24 hours: Othertime points of interest include 6 hours, 72 hours or 5 days.

[0286] Based on the parameters altered by the indicated factors, biomapsare generated for the parameters CD69, alphaEbeta7 (CD103), IL-12Rβ2(CD212), CD40L (CD154), intracellular TNF-α, intracellular IL-2 andCXCR3. Other markers of interest for adding to the biomap include:ICAM-1, alpha4beta7, cutaneous lymphocyte antigen (CLA), CD40L (CD154),OX40 (CD134), FasL (CD178), CTLA-4 (CD152), L-selectin (CD62L), CCR5,CCR6, CCR7, CXCR4, CXCR5, IL-4R (CD124), CD26, CD38, CD30, intracellularIFN-γ, intracellular IL-4, CD25, CCR9, CCR2, CCR4, RANTES, MIP-1beta,CD71, CD223, ICOS, CDw137.

[0287] Parameters on T cells in the culture are analyzed by flowcytometry. Anti-CD3 and anti-CD4 antibodies are used to identify CD4+and CD4− T cells, and non T cells. Antibodies to the selected parametersare used with two additional colors. Readout patterns for T cellscultured with and without SEB or costimulators can be distinguished.

[0288] A database of biomaps is generated from a panel of assaycombinations that include the presence and absence of each biologicallyactive factor; and anti-inflammatory drug compounds including inhibitorsof T cell activation and/or T cell proliferation including calcineurininhibitors, FK506, cyclosporin, mycophenolic acid, methotrexate; as wellas immune stimulatory agents including pathogens or pathogen components,etc. are screened and biomaps generated that show the changes in themarkers with the different agents. Such agents are given in ThePharmacologic Basis of Therapeutics. The biomaps with the known agentsare used to compare to candidate drugs. This allows the recognition ofthe pathway(s) the candidate drug acts on, by comparing the changes inthe level of the specific markers for known drugs affecting knownpathways and the changes observed with the candidate drug. In additionto further add to the utility of the biomap, one may include in thedatabase reference biomaps generated from assay panels containing cellswith genetic constructs that selectively target or modulate specificcellular pathways (e.g. NFAT, calcineurin, NFκB, MAP kinase, etc), orcells that contain known genetic mutations, e.g. Jurkat cell lines thatlack lck, CD45, etc. (Yamasaki, J. Biol. Chem. 272:14787, 1997).

EXAMPLE 19 REGULATORS OF T CELL FUNCTION—ADULT AND MEMORY T CELLS

[0289] The present invention is useful for identifying regulators of Tcell mediated inflammation and immunity. A set of assay combinationsthat reproduces aspects of the response of the adult T cells is used.

[0290] Adult human peripheral blood mononuclear cells are used. Othercells that may replace adult peripheral blood T cells include isolatedpopulations of CD4+, CD8+, TCRgamma/delta, and/or memory T cells; T celllines such as Jurkat, Hut 78, CEM, and T cell clones. Peripheral bloodmononuclear cells are isolated from blood by Ficoll-hypaque densitygradient centrifugation as described (Ponath, JEM 183:2437, 1996). Cellsare then cultured at 106 cells/ml in RPMI containing 10% FBS andStaphylococcal Enterotoxin B (SEB) (1 μg/ml), anti-CD28 (10 ug/ml), andIL-12 (5 ng/ml). In subsequent panels one or more StaphylococcalEnterotoxin E (SEE), or toxic shock syndrome toxin (TSST), or antibodyto CD3 (1 ug/ml) can replace or be included with SEB to provide T cellreceptor stimulation. TCR stimulation through conventional antigens oralloantigen, as in the mixed lymphocyte culture. In subsequent panelsone or more of IL-1 (10 ng/ml), IL-2 (1 ng/ml), IL-10, IL-4 (20 ng/ml),IL-13 (30 ng/ml), TGF-beta (10 ng/ml), anti-CD49d, IL-6, IL-7, IL-15,IL-18; and/or neutralizing antibodies to autocrine factors, IL-4, IFN-γ,IL-2, TNF-α, are added to the initial three factors or may replace theIL-12. Antibodies or ligands for CD49d and CD28 provide costimulatorysignals. Other alternative costimulatory signals of interest that may besubstituted for anti-CD28 and anti-CD49d include antibodies or ligandsto CD5, anti-ICOS, or anti-4-1BB. The TCR stimulus and biologicallyactive factors are then applied for 24 hours: Other time points ofinterest include 6 hours, 72 hours or 5 days.

[0291] Standard concentrations of agents and factors are employed asdescribed in the literature. T cells in the cultures are analyzed byflow cytometry. Based on the parameters altered by the indicatedfactors, biomaps are generated for the parameters CD40L (CD154), CD69,Ox40 (CD134), intracellular γIFN, TNFα, IL-2, FAS ligand (CD178), alphae-integrin (CD103), CTLA4 (CD152), and IL-12receptor beta2 (CD212).Other parameters of interest include CD95, CD45RO, alph4beta7,alpha4beta7, alpha4beta1, L-selectin (CD62L), CCR7, CCR5, CXCR3, CXCR4,CCR6, CXCR5, CCR9, CCR2, CCR4, RANTES, MIP1beta, CD71, CD223, ICOS,CDw137, CD26, CD30, CD38, cutaneous lymphocyte antigen (CLA) and IL-4Ralpha chain.

[0292] Parameters on T cells in the culture are analyzed by flowcytometry. Anti-CD3 and anti-CD4 antibodies are used to identify CD4+and CD4− T cells, and non T cells. CD95, CD45RO and/or CD45RA are usedto identify memory T cells. Antibodies to the selected parameters areused with 2-4 additional colors. Readout patterns for T cells culturedwith and without SEB or costimulators can be distinguished.

[0293] A database of biomaps is generated from a panel of assaycombinations that include the presence and absence of each biologicallyactive factor; and anti-inflammatory drug compounds including inhibitorsof T cell activation and/or T cell proliferation including calcineurininhibitors, FK506, cyclosporin, mycophenolic acid, methotrexate; as wellas immune stimulatory agents including pathogens or pathogen components,etc. are screened and biomaps generated that show the changes in themarkers with the different agents. Such compounds are given in ThePharmacologic Basis of Therapeutics. The biomaps with the known agentsare used to compare to candidate agents. This allows the recognition ofthe pathway(s) the candidate agent acts on, by comparing the changes inthe level of the specific markers for known drugs affecting knownpathways and the changes observed with the candidate agent. In additionto further add to the utility of the biomap, one may include in thedatabase reference biomaps generated from assay panels containing cellswith genetic constructs that selectively target or modulate specificcellular pathways (e.g. NFAT, calcineurin, NFκB, MAP kinase, etc), orcells that contain known genetic mutations, e.g. Jurkat cell lines thatlack lck, CD45, etc. (Yamasaki, J. Biol. Chem. 272:14787, 1997).

EXAMPLE 20 REGULATORS OF T CELL FUNCTION—TH1 RESPONSES

[0294] The present invention is applied for the screening of compoundsthat inhibit the activation of Th1 lymphocytes.

[0295] Human peripheral blood CD4+ T cells are employed. Other cellsthat may be employed include the T cell line KIT-225, human peripheralblood CD3+cells, human cord blood T cells, etc. Cells are isolated fromhuman peripheral blood mononuclear cells utilizing Ficoll-hypaquedensity gradient centrifugation as described (Ponath, JEM 183:2437,1996). Following adherence of cells to plastic, CD4+ cells are isolatedfrom non-adherent cells using Miltenyi magnetic beads as described(Andrew, JI 166:103, 2001). Alternatively, purified human CD4+ T cellsare obtained from a commercial source (Clonetics Corp.). Purified CD4+lymphocytes are then cultured at 106 cells/ml in DMEM containing 10% FBSand anti-CD3 (1 μg/ml), anti-CD28 (10 μg/ml), IL-2 (4 ng/ml), IL-12 (5ng/ml) and neutralizing antibody to IL4 (1 μg/ml) for 3 days. Insubsequent panels one or more of PHA (1 μg/ml) IL-1 (20 ng/ml), IL-6,IL-7, neutralizing antibody to IL4, are added to the initial threefactors or may replace one of the three factors. Other time points ofinterest include 5 and 7 days.

[0296] Based on the parameters altered by the indicated factors, biomapsare generated for the parameters CD40L (CD154), alpha4beta7, cutaneouslymphocyte antigen (CLA), CXCR3 (CD183), IL-12receptor beta2 (CD212),intracellular IFN-γ, intracellular TNF-α, and intracellular IL-2. Othermarkers of interest for adding to the biomap include: ICAM-1, OX40(CD134), FasL (CD178), CTLA4 (CD152), L-selectin (CD62L), CCR5 (CD195),CCR6, CCR7 (CDw197), CXCR4 (CD184), CXCR5, IL-4R (CD124), CD26, CD38,CD30, P-selectin-ligand activity, intracellular IL-4, intracellur IL-5and intracellular IL-13.

[0297] Parameters on T cells in the culture are analyzed by flowcytometry. Anti-CD3 and anti-CD4 antibodies are used to identify CD4+and CD4− T cells, and non T cells. CD45RO and/or CD45RA are used toidentify memory T cells. Antibodies to the selected parameters are usedwith 24 additional colors. Readout patterns for T cells cultured withand without SEB or costimulators can be distinguished.

[0298] A database of biomaps is generated from a panel of assaycombinations that include the presence and absence of each biologicallyactive factor; and anti-inflammatory drug compounds including inhibitorsof T cell activation and/or T cell proliferation including calcineurininhibitors, FK506, cyclosporin, mycophenolic acid, methotrexate; as wellas immune stimulatory agents including pathogens or pathogen components,etc. are screened and biomaps generated that show the changes in themarkers with the different agents. Such compounds are given in ThePharmacologic Basis of Therapeutics. The biomaps with the known agentsare used to compare to candidate agents. This allows the recognition ofthe pathway(s) the candidate agent acts on, by comparing the changes inthe level of the specific markers for known drugs affecting knownpathways and the changes observed with the candidate agent. In additionto further add to the utility of the biomap, one may include in thedatabase reference biomaps generated from assay panels containing cellswith genetic constructs that selectively target or modulate specificcellular pathways (e.g. NFAT, calcineurin, NFkB, MAP kinase, etc), orcells that contain known genetic mutations, e.g. Jurkat cell lines thatlack lck, CD45, etc. (Yamasaki, J. Biol. Chem. 272:14787, 1997).

EXAMPLE 21 Regulators of T Cell Function—Th2 Responses

[0299] The present invention is applied for the screening of compoundsthat inhibit the activation of Th2 lymphocytes.

[0300] Human peripheral blood CD4+ T cells are employed. Other cellsthat may be employed include human peripheral blood CD3+ cells. Cellsare isolated from human peripheral blood mononuclear cells utilizingFicoll-hypaque density gradient centrifugation as described (Ponath, JEM183:2437, 1996). Following adherence of cells to plastic, CD4+ cells areisolated from non-adherent cells using Miltenyi magnetic beads asdescribed (Andrew, JI 166:103, 2001). Purified CD4+ lymphocytes are thencultured at 10⁶ cells/ml in DMEM containing 10% FBS and anti-CD3 (1μg/ml), anti-CD28 (10 μg/ml) IL-2 (4 ng/ml), IL-4 (5 ng/ml) andneutralizing antibody to IFN-γ (1 μg/ml) for 3 days. In subsequentpanels one or more of PHA (1 μg/ml) IL-1 (20 ng/ml), IL-6, IL-7, IL-13,neutralizing antibody to IL-12, are added to the initial three factorsor may replace one of the three factors. Other time points of interestinclude 5 and 7 days.

[0301] Based on the parameters altered by the indicated factors, biomapsare generated for the parameters alpha4beta7, alphaEbeta7, cutaneouslymphocyte antigen (CLA), CCR3, intracellular IL-2, intracellular TNF-α,IL-4, IL-5 and IL-13. Other markers of interest for adding to the biomapinclude: ICAM-1, CD40L, OX40 (CD134), FasL (CD178), CTLA-4 (CD152),L-selectin (CD62L), CCR3, CCR5, CCR6, CCR7, CXCR4, CXCR5, IL-4R (CD124),CD26, CD38, CD30, P-selectin ligand activity and intracellular IFN-γ.

[0302] Parameters on T cells in the culture are analyzed by flowcytometry. Anti-CD3 and anti-CD4 antibodies are used to identify CD4+and CD4− T cells, and non T cells. CD45RO and/or CD45RA are used toidentify memory T cells (Teraki, J. Immunol 159:6018, 1997; Waldrop, J.Immunol. 161:5284, 1998; Picker, Blood, 86:1408, 1995). Antibodies tothe selected parameters are used with 2-4 additional colors. Readoutpatterns for T cells cultured with and without SEB or costimulators canbe distinguished.

[0303] A database of biomaps is generated from a panel of assaycombinations that include the presence and absence of each biologicallyactive factor; and anti-inflammatory drug compounds including inhibitorsof T cell activation and/or T cell proliferation including calcineurininhibitors, FK506, cyclosporin, mycophenolic acid, methotrexate; as wellas immune stimulatory agents including pathogens or pathogen components,etc. are screened and biomaps generated that show the changes in themarkers with the different agents. Such compounds are given in ThePharmacologic Basis of Therapeutics. The biomaps with the known agentsare used to compare to candidate agents. This allows the recognition ofthe pathway(s) the candidate agent acts on, by comparing the changes inthe level of the specific markers for known drugs affecting knownpathways and the changes observed with the candidate agent. In additionto further add to the utility of the biomap, one may include in thedatabase reference biomaps generated from assay panels containing cellswith genetic constructs that selectively target or modulate specificcellular pathways (e.g. NFAT, calcineurin, NFkB, MAP kinase, etc), orcells that contain known genetic mutations, e.g. Jurkat cell lines thatlack lck, CD45, etc. (Yamasaki, J. Biol. Chem. 272:14787, 1997).

EXAMPLE 22 REGULATORS OF MONOCYTE FUNCTIONS

[0304] The present invention is applied for the screening of compoundsfor modulating monocyte/macrophage functions.

[0305] Human peripheral blood monocytes are used. Other cells that mayreplace human peripheral blood monocytes include: bone-marrow derivedmonocytes, monocytes isolated by elutriation or negative magnetic beadisolation, and monocyte cell lines THP-1 or U937. Four×106 peripheralblood mononuclear cells/ml are cultured in RPMI containing 10% fetalbovine serum for 2 hours. Non-adherent lymphocytes are removed by gentlewashing. The following are then applied for 24 hours: IL-1 (1 ng/ml),IFN-γ (50 ng/ml) and TGF-beta (10 ng/ml) (Dietz, Basic Res. Cardiology93 Suppl2:101, 1998; Lommi, Eur. Heart. J. 18:1620, 1997; Jafri, Semin.Thromb. Hemost. 23:543, 1997). In subsequent panels one or more oflipopolysaccharide (10 ng/ml), GM-CSF (10 ng/ml), TNF-α (5 ng/ml), IL-4(20 ng/ml), IL-13 (30 ng/ml), osteopontin (10 ng/ml), thrombin (10U/ml), CD40L, oxidized LDL (100 ug/ml), or minimally modified LDL areadded to the initial three factors or may replace one of the threefactors (Brown, J Clin Endocrinol Metab, 85:336, 2000; Ashkar, Science287:860, 2000; de Boer, J. Pathol. 188:174, 1999; Berliner, J. Clin.Invest. 85:1260, 1990). Standard concentrations of agents are employedas described in the literature (Kaplanski, J. Immunol 158:5435, 1997;Hofman, Blood 92:3064, 1998; Li, Circulation 102:1970, 2000; Essler, JBC274:30361, 1999; Brown, J Clin Endocrinol Metab, 85:336, 2000). Based onthe parameters altered by the indicated factors, biomaps are generatedfor the parameters ICAM-1, Mac-1 (CD11b/CD18), IL-8, HLA-DR, TNF-α,IL-12 and MCP-1 (Devaux, Eur. Heart J. 18:470, 1997; Kessler, DiabetesMetab. 24:327, 1998; Becker, Z. Kardiol. 89:160, 2000; Kaplanski, J.Immunol. 158:5435, 1997; Li, Circulation 102:1970, 2000). Other markersof interest for adding to the biomap include CD14, PAI-1, urokinase-typeplasminogen activator receptor (uPAR, CD87), IL-10, IL-18, tissuefactor, fibrinogen-binding activity, MIG chemokine, TARC, MDC, RANTES,CD25, CD80, CD86, CD40 and CD36 (Paramo, Br. Med. J. 291:573, 1985;Fukuhara, Hypertension 35:353, 2000; Noda-Heiny, Arterioscler ThrombVasc. Biol. 15:37, 1995; de Prost, J. Cardiovasc. Pharmacol., 25Suppl2:S114, 1995; van de Stolpe, Thromb Haemost 75:182, 1996; Mach, J.Clin. Invest., 104:1041, 1999; Nicholson, Ann. N.Y. Acad. Sci., 902:128,2000). A database of biomaps is generated from a panel of assaycombinations that include known anti-atherogenic agents includingstatins and others, are screened and a biomap generated that shows thechanges in the markers with the different anti-cancer agents. Suchcompounds are given in The Pharmacologic Basis of Therapeutics. Thebiomaps with the known agents are used to compare to candidate agents.This allows the recognition of the pathway(s) the candidate drug actson, by comparing the changes in the level of the specific markers forknown drugs affecting known pathways and the changes observed with thecandidate drug. In addition to further add to the utility of the biomap,one may include in the database reference biomaps generated from assaypanels containing cells with genetic constructs that selectively targetor modulate specific cellular pathways (e.g. NFκB, MAP kinase, etc), orcells that contain known genetic mutations (e.g. CD36-deficiency, Yanai,Am. J. Med. Genet. 93:299, 2000, etc.).

[0306] It is to be understood that this invention is not limited to theparticular methodology, protocols, cell lines, animal species or genera,and reagents described, as such may vary. It is also to be understoodthat the terminology used herein is for the purpose of describingparticular embodiments only, and is not intended to limit the scope ofthe present invention which will be limited only by the appended claims.

[0307] As used herein the singular forms “a”, “and”, and “the” includeplural referents unless the context clearly dictates otherwise. Alltechnical and scientific terms used herein have the same meaning ascommonly understood to one of ordinary skill in the art to which thisinvention belongs unless clearly indicated otherwise.

[0308] The examples are put forth so as to provide those of ordinaryskill in the art with a complete disclosure and description of how tomake and use the subject invention, and are not intended to limit thescope of what is regarded as the invention. Efforts have been made toensure accuracy with respect to the numbers used (e.g. amounts,temperature, concentrations, etc.) but some experimental errors anddeviations should be allowed for. Unless otherwise indicated, parts areparts by weight, molecular weight is average molecular weight,temperature is in degrees centigrade; and pressure is at or nearatmospheric.

[0309] All publications mentioned herein are incorporated herein byreference for the purpose of describing and disclosing, for example, thecompounds and methodologies that are described in the publications whichmight be used in connection with the presently described invention. Thepublications discussed above and throughout the text are provided solelyfor their disclosure prior to the filing date of the presentapplication. Nothing herein is to be construed as an admission that theinventors are not entitled to antedate such disclosure by virtue ofprior invention.

1 2 1 22 DNA Artificial Sequence antisense oligonucleotides for TNF-R1 1aggtcaggca cggtggagag gc 22 2 25 DNA Artificial Sequence beta-globincontrol oligonucleotides 2 cctcttacct cagttacaat ttata 25

What is claimed is:
 1. A method for analyzing the effect of abiologically active agent on a cell in a cell culture using at least twocell culture assay combinations, wherein at least one cell culturecomprises an assay combination with at least two factors sufficient toprovide a physiological state of interest involving at least twopathways in said cell in said cell culture; and at least one cellculture is a cell culture lacking said factors, said method comprising:contacting one or more of said cell cultures with said biologicallyactive agent; incubating said cell cultures in said respectiveenvironments; and measuring parameters whose levels respond to saidpathways; whereby the differences in said levels is indicative of theeffect of said biologically active agent on said cell culture.
 2. Themethod according to claim 1, wherein one of said assay combinationssimulates an in vivo physiological state.
 3. The method according toclaim 1, wherein one of said cell cultures is a control cell cultureselected from the group consisting of: a basal cell culture in theabsence of said factors; a basal cell culture in the absence of saidfactors and in the presence of an agent of known physiological activity;said cell culture in the presence of said factors, or said cell culturein the presence of said factors and a compound of known physiologicalactivity.
 4. A method for evaluating the effect of a biologically activeagent on a cell culture simulating a physiological state of cells invivo, whereby said physiological state is simulated by employing thesame type of cells in the culture medium as in said physiological state,in the presence of a medium containing factors simulating thephysiological state environment to provide an assay combination, andparameters are measured that result from a plurality of pathwaysassociated with said physiological state, said method comprising: addingsaid biologically active agent to said assay combination and incubatingsaid assay combination for sufficient time for said agent to affect saidcells; measuring a sufficient number of a plurality of parametersassociated with said physiological condition to ensure that at least twopathways are involved in the regulation of the production of saidparameters; and comparing the level of parameters observed in thepresence of said agent with a control assay combination; whereby theeffect of said agent on said cells in culture is predictive of theeffect of said agent on said physiological state in vivo.
 5. The methodaccording to claim 4, wherein said physiological state environmentcomprises said biologically active agent and said control assaycombination is free of said agent.
 6. The method according to claim 4,wherein said cell culture comprises a plurality of different cell typesassociated with said physiological state.
 7. A method for preparing abiomap for a plurality of pathways associated with a physiological stateof interest of cells in a cell culture, said method comprising:formulating a test cell culture assay combination in said physiologicalstate of interest as a result of adding to said cell culture a pluralityof factors in an amount and incubating for a time sufficient to inducesaid physiological state and a control cell culture differing in atleast one component from said test cell culture, wherein said componentcan be a factor, a biologically active agent or other environmentalcondition; measuring at least four parameters associated with saidplurality of pathways and comparing the measurement of said at leastfour parameters with the measurement from a control cell culture, andrecording said measurements of said test cell culture and said controlcell culture to produce a biomap.
 8. A method for preparing a biomapdataset for a plurality of pathways associated with a plurality ofphysiological states of interest of cells in cell culture, said methodcomprising: formulating a panel of cell culture assay combinations insaid physiological states of interest as a result of adding to saidcultures in said assay combinations a plurality of factorsin an amountand for a period of time sufficient to induce said physiological stateof interest, wherein at least one of said assay combination is a testassay combination and one a control cell culture differing in at leastone component from said test cell culture; wherein said component can bea factor, a biologically active agent or other environmental conditionmeasuring at least four parameters associated with said plurality ofpathways; comparing the measurement of said at least four parameterswith the measurement from a control cell culture, and recording saidmeasurements of said test cell culture and said control cell culture toproduce a biomap.
 9. The method according to claim 8, further comprisingthe step of compiling a plurality of said biomaps in a database.
 10. Amethod for characterization of a biologically active agent according toits effect on cellular signaling pathways, the method comprising:contacting a panel of cell culture assay combinations with said agent;recording changes in at least four different cellular parameter readoutsas a result of introduction of said agent; deriving a biomap datasetfrom said changes in parameter readouts, wherein said biomap comprisesdata normalized to control data on the same cell type under controlconditions, and wherein output parameters are optimized so that the setof data in the biomap is sufficiently informative that it candiscriminate the mode of action or functional effect of an agent;comparing said biomap dataset to a reference biomap dataset to determinethe presence of variation, wherein the presence of variation indicates adifference in the effect of the agent on a cellular signaling pathway.11. The method according to claim 10, wherein said panel of cellscomprises at least one assay combination comprising two or more factorsacting on said cells.
 12. The method according to claim 11, wherein saidpanel of cells comprises at least one assay combination simulating an invivo physiological state.
 13. The method according to claim 11, whereinsaid comparing step comprises: comparing said biomap dataset for asingle biologically active agent to a plurality of biomap datasets in adatabase to determine whether said variation matches a pattern in saiddatabase, thereby characterizing said agent according to its effect on acellular signaling pathway.
 14. A method according to claim 1, whereinsaid cells are primary cells.
 15. A method according to claim 1, whereinsaid cells are selected from the group consisting of endothelial cells,leukocytes, neoplastic cells and epithelial cells.
 16. A methodaccording to claim 1, wherein said cells are genomically modified cells.17. A method according to claim 1, wherein said biologically activeagent is an organic compound.
 18. A method according to claim 1, whereinsaid biologically active agent is a genetic agent.
 19. A methodaccording to claim 1, wherein said cells are endothelial cells and atleast one of said assay combinations comprises at least two of TNF-α,IFN-γ, IL-4, IL-13, histamine and IL-1 activities; and said parameterscomprise at least two of ICAM-1, VCAM-1 E-selectin, P-selectin, IL-8,MCP-1, Eotaxin, CD31, HLA-DR, IP-10 and MIG.
 20. A method according toclaim 1, wherein said cells are endothelial and T cells in a cocultureand at least one of said assay combinations comprises at least two ofTNF-α, IFN-γ, IL-4, IL-13, histamine and IL-1 activities; and saidparameters comprise at least two of ICAM-1, VCAM-1 E-selectin,P-selectin, IL-8, MCP-1, Eotaxin, CD31, HLA-DR, IP-10 and MIG.
 21. Amethod according to claim 1, wherein said cells are epithelial cells andat least one of said assay combinations comprises at least two of TNF-α,IFN-γ, IL-9, IL-17 and IL-1 activities; and said parameters comprise atleast two of ICAM-1, IL-8, Mip-3alpha, MCP-1, E-cadherin, HLA-DR, IP-10and MIG.
 22. A method according to claim 1, wherein said cells are coloncancer cells and at least one of said assay combination comprises atleast two of IGF-II, TNF-α, IFN-γ, IL-1, TGF-β, EGF, and IL-6activities; and said parameters comprise at least two of ICAM-1, HLA-11,CD44, carcinoembryonic antigen (CEA), EGF-receptor, E-cadherin, CD87 andα₅β₁.
 23. A method according to claim 1, wherein said cells are prostatecancer cells and at least one of said assay combinations comprises atleast two of 5-dihydrotestosterone, TNF-α, IL-6, IL-1, TGF-β, EGF, andIGF-II activities; and said parameters comprise at least two of prostatespecific antigen (PSA), E-cadherin, IL-8, vascular endothelial growthfactor (VEGF), epidermal growth factor receptor, and Her-2/neu.
 24. Amethod according to claim 1, wherein said cells are breast cancer cellsand at least one of said assay combinations comprises at least two ofestrogen, IL-4, antibody to Her-2/neu, IL-1, TNF-α, IFN-γ, IL-4, IL-13,TGF-β, EGF and IL-6 activities; and said parameters comprise at leasttwo of ICAM-1, IL-8, MCP-1, E-cadherin, HLA-II, CD44, carcinoembryonicantigen (CEA), EGF-receptor, poly-Ig receptor, uPAR (CD87) and α₅β₁. 25.A method according to claim 1, wherein said cells are endothelial cellsand at least one of said assay combinations comprises at least two ofVEGF, FGF, EGF, TNF-α, IL-4, IL-13, histamine, IL-8 and IL-1 activities;and said parameters comprise at least two of alphavbeta3, IL-8, VCAM-1,E-selectin, KDR, uPAR (CD87), ICAM-1, P-selectin, thrombomodulin, TissueFactor, MMP-2, MMP-3, α₅β₁, α_(v)β₅, CD105 and CD31.
 26. A methodaccording to claim 1, wherein said cells are endothelial cells and atleast one of said assay combinations comprises at least two ofangiotensin-II, TNF-α, thrombin, IFN-γ, IL-4, IL-13, histamine, PDGF,oxidized LDL and IL-1 activities; and said parameters comprise at leasttwo of ICAM-1, VCAM-1 E-selectin, P-selectin, IL-8, MCP-1,platelet-derived growth factor (PDGF), MIG, PAI-1, angiotensinconverting enzyme (ACE), urokinase-type plasminogen activator receptor(uPAR), tissue factor, and CD36.
 27. A method according to claim 1,wherein said cells are T lymphocytes and at least one of said assaycombinations comprises at least two of Staphylococcal enterotoxin B,anti-CD28, anti-CD3, anti-CD49d, IL-12, IL-1, 11-2, IL-4, IL-6, IL-7,IL-13, IL-15, IL-18, and TGFβ activities; and said parameters compriseat least two of CD69, alphaEbeta7 (CD103), alpha4beta7, IL-12Rβ2(CD212), CD178 (FasL), CD40L (CD154), intracellular TNF-α, intracellularIL-2, intracellular IFN-γ, intracellular IL-4, CCR3 and CXCR3.
 28. Ascreening system for determining the effect of a biologically activeagent on a physiological state or cell pathways of interest, said systemcomprising a panel comprising at least two cell culture assaycombinations comprising cells and at least two factors affecting atleast four pathways for inducing said physiological state of interest onsaid cells, wherein at least one of said assay combinations comprisessaid biologically active agent; assay reagents for measuring at leasttwo parameters associated with said pathways; and a data processor foranalyzing the data from said biological culture in relation to at leastone control biological culture of known activity.
 29. The systemaccording to claim 28, wherein said data processor comprises a pluralityof biomap datasets in a database, wherein said biomap datasets areprepared according to the method set forth in claim
 7. 30. A panelcomprising at least two cell culture assay combinations comprisingendothelial cells, wherein at least one of said assay combinationscomprises a sufficient amount of TNF-α, IFN-γ and IL-1 to induce aninflammatory response from said endothelial cells; and a test agentpresent in at least one of said assay combinations.
 31. A panelcomprising at least two cell culture assay combinations comprisingneoplastic breast cancer cells, wherein at least one of said assaycombinations comprises a sufficient amount of at least three ofestrogen, IL-4, antibody to Her-2/neu, and IL-1b activities that inducesaid test breast cancer cells to simulate breast cancer cells in vivo;and a test agent present in at least one of said assay combinations. 32.A method according to claim 1, wherein one or more of said assaycombinations comprises a biologically active agent of knownphysiological activity, and a test agent.